Genetic neuroscience: How human genes and alleles shape neuronal phenotypes

遗传神经科学：人类基因和等位基因如何塑造神经元表型

• 批准号: 9757833
• 负责人: Paola Arlotta
• 金额: $ 412.91万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-20 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9757833
• 关键词: Affect; Alleles; Architecture; Area; Awareness; Biological; Biological Assay; Biology; Brain; Brain Diseases; California; Cell Differentiation process; Cell Line; Cell physiology; Cells; Cellular biology; Communities; Computer Analysis; Data; Data Science; Data Set; Dimensions; Disease; Engineering; Environment; Experimental Models; Functional disorder; Genes; Genetic; Genetic Transcription; Genetic study; Goals; Human; Human Genetics; Individual; Institutes; Investments; Ion Channel; Lead; Libraries; Machine Learning; Mathematics; Measurement; Measures; Mental disorders; Methods; Microglia; Molecular; Molecular Biology; Mutation; Nervous system structure; Neurobiology; Neurons; Neurosciences; Organoids; Penetrance; Phenotype; Physiological; Physiology; Population; Process; Property; Proteins; Psychiatry; RNA; Regenerative Medicine; Resources; Risk; Sampling; Science; Scientist; Shapes; System; Technology; Test Result; Testing; Therapeutic; Time; Variant; Work; analytical tool; cell type; computer science; computing resources; cost; cytokine; excitatory neuron; experimental study; genetic information; human data; improved; induced pluripotent stem cell; inhibitory neuron; innovation; insight; loss of function mutation; multidimensional data; neurophysiology; next generation; novel; protein expression; protein function; rare variant; response; risk variant; stem cell biology; translational neuroscience; whole genome

Genetic studies have identified many specific loci with significant associations to psychiatric disorders. However, unless we can develop useful approaches for systematically turning genetic information into neurobiological insights about brain disorders, there is a danger that costly and hard-won genetic findings will not be exploitable to understand pathophysiology and generate important therapeutic hypotheses. The goal of our collaborative, interdisciplinary effort is to develop powerful, generalizable approaches for discovering how risk variants for psychiatric disorders shape neurobiological processes at multiple levels of analysis, and to identify the processes whose dysregulation underlies disease. To do this, we propose to develop new experimental and inferential systems to bridge a longstanding gap between human genetics and experimental biology. We aim to identify biological causes and effects that span the genetic, molecular, and cellular levels of the nervous system. Our interdisciplinary team will develop new experimental systems that measure genetic influences across levels of analysis (RNA, proteins, and cellular function including physiology) in precise, scalable, well- controlled ways. We will make use of emerging cellular systems including three-dimensional cortical spheroids and organoids, and radically novel “population in a dish” experimental systems that collect data on cells from hundreds of donors in a shared environment, inferring donor identity at the time of phenotypic readout. The analysis of such systems in turn requires sophisticated inferential strategies and new ideas from computer science. We propose to develop and widely share experimental and computational resources, including cell lines, methods, datasets, and analytic tools. The successful completion of this work will identify key neurobiological processes for multiple psychiatric disorders, and fortify many other scientists in making such connections in their own work. We hope in so doing to create a new kind of interdisciplinary science that – by combining the strengths of data-driven, unbiased human genetics with the power of emerging experimental systems – transforms the rate at which human- genetic leads lead to insights about disease mechanisms.

遗传学研究已经确定了许多与精神疾病显着相关的特定位点。 然而，除非我们能够开发出有用的方法来系统地将遗传信息转化为 关于脑部疾病的神经生物学见解，存在着代价高昂且来之不易的遗传发现可能会 不能用于理解病理生理学并产生重要的治疗假设。 我们跨学科合作的目标是开发强大的、通用的方法 发现精神疾病的风险变异如何在多个层面塑造神经生物学过程 分析，并确定其失调导致疾病的过程。为此，我们建议： 开发新的实验和推理系统，以弥合人类遗传学和基因学之间长期存在的差距 我们的目标是确定跨越遗传、分子、 和神经系统的细胞水平。 我们的跨学科团队将开发新的实验系统来测量跨学科的遗传影响 精确、可扩展、良好的分析水平（RNA、蛋白质和细胞功能，包括生理学） 我们将利用新兴的细胞系统，包括三维皮质球体。 和类器官，以及全新的“培养皿中的群体”实验系统，该系统收集来自 数百名捐赠者处于共享环境中，在读出表型时推断捐赠者身份。 反过来，对此类系统的分析需要复杂的推理策略和计算机的新想法 我们建议开发并广泛共享实验和计算资源，包括细胞资源。 线条、方法、数据集和分析工具。 这项工作的成功完成将确定多种精神病学的关键神经生物学过程 疾病，并加强许多其他科学家在他们自己的工作中建立这种联系，我们希望这样做。 创建一种新的跨学科科学——通过结合数据驱动、公正的优势 人类遗传学与新兴实验系统的力量——改变了人类遗传学的速度 遗传线索导致对疾病机制的深入了解。