Beyond GWAS: High Throughput Functional Genomics & Epigenome Editing to Elucidate the Effects of Genetic Associations for Schizophrenia

项目摘要 精神分裂症（SCZ）基因组学取得了前所未有的进展。十年前，也许有一个 可靠的发现，现在有约270个位点符合显著性和重复性的共识标准。作为 对于其他复杂的精神疾病，所识别的区域绝大多数是非编码的， 这强烈表明基因调控元件中的遗传变异是主要的机制贡献者。 对这些监管机制的进一步调查由于以下能力的根本差距而无法进行： 识别、表征和量化大脑相关的调节元件，以及对如何调节的有限理解 这些元素中的遗传变异影响它们的功能。 为了解决这一知识差距，本项目将全面识别、表征、量化和验证 神经元细胞中的非编码功能性非编码调控元件和变体。的中心假设 这一观点认为，非编码变异通过直接改变 大脑中的调节元件。提出这项研究的动机是， 精神疾病的发病机制有可能转化为更好的诊断和治疗。 由一支在精神疾病、功能基因组学、 技术发展和统计遗传学，这一假设将通过完成三个具体的测试， 目标：1）全面整合不同的数据类型，以生成“连接”的假设 精神病遗传结果到特定基因; 2）进行高通量CRISPR表观基因组编辑 在自然生物背景下测试目标1假设的屏幕; 3）发展机械理解， 使用TF结合试验和来自SCZ的iPS衍生神经元验证功能性非编码SCZ风险变体 遗传风险评分高的病例。 我们的方法是创新的，因为它使用了一套高度互补和多样化的实验方法， 方法来推动有针对性的遗传和功能研究相关的SCZ的监管机制。 在这样做的过程中，拟议的研究提供了一条急需的前进道路，以了解非编码如何 变异导致复杂的人类表型。

Project Summary Schizophrenia (SCZ) genomics has achieved unprecedented advances. A decade ago, there was perhaps one solid finding, and there are now ~270 loci that meet consensus criteria for significance and replication. As observed for other complex psychiatric disorders, the identified regions are overwhelmingly noncoding, strongly suggesting that genetic variation in gene regulatory elements is a major mechanistic contributor. Further investigation of those regulatory mechanisms is precluded by a fundamental gap in the ability to identify, characterize, and quantify brain-relevant regulatory elements, and limited understanding of how genetic variation within those elements influences their function. To address this knowledge gap, this project will comprehensively identify, characterize, quantify, and validate noncoding functional noncoding regulatory elements and variants in neuronal cells. The central hypothesis of the proposal is that noncoding variation contributes to psychiatric disorders by directly altering the function of regulatory elements in the brain. The motivation for the proposed study is that identifying regulatory mechanisms of psychiatric disorders has the potential to translate into improved diagnosis and treatment. Powered by a team with strong interdisciplinary expertise in psychiatric disorders, functional genomics, technology development, and statistical genetics, this hypothesis will be tested by completing three specific aims: 1) Comprehensive integration of diverse data types to generate hypotheses that “connect” psychiatric genetic results to specific genes; 2) perform high-throughput CRISPR epigenome editing screens to test Aim 1 hypotheses in a natural biological context; 3) Develop mechanistic understanding and validate functional noncoding SCZ risk variants using TF binding assays and iPS-derived neurons from SCZ cases with high genetic risk scores. Our approach is innovative because it uses a highly complementary and diverse set of experimental approaches to drive targeted genetic and functional investigation into regulatory mechanisms relevant for SCZ. In doing so, the proposed research provides a much-needed path forward to understand how noncoding variation contributes to complex human phenotypes.