Decoding schizophrenia-From GWAS to functional regulatory variants

描述（由申请人提供）：全基因组关联（GWA）研究已经确定了>100个基因组区域与精神分裂症风险有关。如对其他复杂病症所观察到的，所鉴定的区域绝大多数是非编码的，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。这些调控机制的进一步调查是排除了一个根本的差距，在识别大脑中的疾病特异性调控元件的能力，以及有限的了解如何在这些元素的遗传变异影响其功能。为了解决这一知识差距，该项目将全面识别，表征和验证与精神分裂症相关的脑组织中的非编码功能调控元件。该提案的核心假设是，非编码变异通过直接改变大脑中调节元件的功能而导致精神分裂症。这项拟议研究的动机是，确定精神分裂症的调节机制有可能转化为改善这种常见的慢性衰弱性疾病的诊断和治疗。由一个在精神疾病、功能基因组学、比较灵长类基因组学和统计遗传学方面具有强大跨学科专业知识的团队提供支持，该假设将通过完成三个具体目标来验证：1）使用ATAC-seq从100名精神分裂症患者和100名对照中全面鉴定三个脑区域中的活性基因调控元件; 2）鉴定影响染色质可及性和基因表达的染色质QTL（cQTL），并使用最新的PGC GWA大型分析结果进行靶向关联测试; 3）使用高通量转录因子基因表达测定法对调控变体功能进行优先级排序和定量，并通过基因组编辑进行验证。这种方法是创新的，因为它利用了一套高度互补和多样化的实验方法来推动有针对性的遗传和功能研究精神分裂症的调控机制。最终，产生的数据以及开发的实验和统计方法将使其他疾病和疾病的相关研究成为可能。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，以了解非编码变异如何有助于复杂的人类表型。

DESCRIPTION (provided by applicant): Genome-wide association (GWA) studies have identified >100 regions of the genome that contribute to risk for schizophrenia. As observed for other complex disorders, the identified regions are overwhelmingly non- coding, 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 disorder-specific regulatory elements in the brain, and limited understand of how genetic variation within those elements influences their function. To address that knowledge gap, this project will comprehensively identify, characterize, and validate non-coding functional regulatory elements in brain tissues relevant to schizophrenia. The central hypothesis of the proposal is that non-coding variation contributes to schizophrenia by directly altering the function of regulatory elements in the brain. The motivation for the proposed study is that identifying regulatory mechanisms of schizophrenia has the potential to translate into improved diagnosis and treatment of this common, chronically debilitating disorder. Powered by a team with strong interdisciplinary expertise in psychiatric disorders, functional genomics, comparative primate genomics, and statistical genetics, this hypothesis will be tested by completing three specific aims: 1) Comprehensively identify active gene regulatory elements in three brain regions from 100 schizophrenia cases and 100 controls using ATAC-seq; 2) Identify chromatin QTLs (cQTLs) that impact chromatin accessibility and gene expression, and perform targeted association tests using the most up to date PGC GWA mega analysis results; 3) Prioritize and quantify regulatory variant function using high-throughput reporter-gene expression assays, and validate by genome editing. The approach is innovative because it utilizes a highly complementary and diverse set of experimental approaches to drive targeted genetic and functional investigation into the regulatory mechanisms of schizophrenia. Ultimately, the data produced and the experimental and statistical approaches developed will enable related studies of other disorders and diseases. In doing so, the proposed research provides a much-needed path forward to understand how non- coding variation contributes to complex human phenotypes.