Decoding schizophrenia-From GWAS to functional regulatory variants

描述(由申请人提供)：全基因组关联(GWA)研究已经确定了基因组的100个区域，这些区域有助于精神分裂症的风险。就像对其他复杂疾病的观察一样，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的遗传变异是一个主要的机制贡献因素。由于在识别大脑中特定于障碍的调控元素的能力方面存在根本差距，以及对这些元素内的遗传变异如何影响其功能的了解有限，因此无法进一步研究这些调控机制。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节元件。该提议的中心假设是，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。拟议研究的动机是，识别精神分裂症的调节机制有可能转化为改善这种常见的、慢性衰弱的疾病的诊断和治疗。这一假说将由一个在精神障碍、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跨学科专业知识的团队提供支持，通过完成三个具体目标来验证：1)使用ATAC-SEQ从100例精神分裂症患者和100名对照组中全面确定三个大脑区域中活跃的基因调控元件；2)确定影响染色质可及性和基因表达的染色质QTL(CQTL)，并利用最新的PGC GWA mega分析结果执行有针对性的关联测试；3)使用高通量报告基因表达分析来确定调控变异功能的优先级并进行量化，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有针对性的遗传和功能研究。最终，产生的数据以及开发的实验和统计方法将使其他障碍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亟需的前进道路，以了解非编码变异是如何导致复杂的人类表型的。

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.