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个与精神分裂症风险相关的基因组区域。正如在其他复杂疾病中观察到的那样，鉴定的区域绝大多数是非编码的，这强烈表明基因调控元件的遗传变异是一个主要的机制因素。由于无法识别大脑中特定疾病的调节元件，以及对这些元件的遗传变异如何影响其功能的理解有限，因此无法对这些调节机制进行进一步的研究。为了解决这一知识缺口，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节元件。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。提出这项研究的动机是，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疾病的诊断和治疗。该团队在精神疾病、功能基因组学、比较灵长类基因组学和统计遗传学方面拥有强大的跨学科专业知识，该团队将通过完成三个特定目标来验证这一假设：1)使用ATAC-seq全面识别来自100名精神分裂症患者和100名对照组的三个大脑区域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QTLs (cQTLs)，并使用最新的PGC GWA mega分析结果进行靶向关联检测；3)利用高通量报告基因表达试验确定调控变异功能的优先级和量化，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对精神分裂症调节机制的靶向遗传和功能研究。最终，所产生的数据以及所制定的实验和统计方法将使对其他失调和疾病的相关研究成为可能。在此过程中，提出的研究为理解非编码变异如何促进复杂的人类表型提供了一条急需的途径。

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.