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

超越 GWAS：高通量功能基因组学

基本信息

批准号：
10573335
负责人：
GREGORY E CRAWFORD
金额：
$ 159.92万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2026-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10573335
关键词：
3-Dimensional ATAC-seq Address Alleles Awareness Binding Binding Proteins Binding Sites Biological Biological Assay Biology Body mass index Brain Brain region Cell Nucleus Cells ChIP-seq Chromatin Clustered Regularly Interspaced Short Palindromic Repeats Collaborations Complex Consensus DNA Data Development Diagnosis Diagnostic Disparate Elements Enhancers Epigenetic Process Exons Funding Gene Expression Genes Genetic Genetic Research Genetic Risk Genetic Variation Genome Genomics Goals Grant Haplotypes Heritability Hi-C Human Individual Induced pluripotent stem cell derived neurons Intervention Investigation Knowledge Machine Learning Magnetic Resonance Imaging Mental disorders Motivation Mutation Neurons Non-Insulin-Dependent Diabetes Mellitus Organoids Pathway interactions Patients Pattern Phenotype Proteomics Quantitative Trait Loci Regulator Genes Regulatory Element Repression Research Risk Schizophrenia Science Solid Sweden Synapses Tail Testing Therapeutic Translating Untranslated RNA Update Validation Variant Work autism spectrum disorder brain volume cell type disorder risk diverse data epigenome epigenome editing excitatory neuron exome sequencing follow-up functional genomics genetic architecture genetic association genome editing genome wide association study genomic data high risk histone modification improved induced pluripotent stem cell innovation insight mind control mouse model nerve stem cell pharmacologic promoter protein protein interaction psychiatric genomics psychogenetics risk variant schizophrenia risk screening single-cell RNA sequencing technology development trait transcription factor

项目摘要

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.

项目概要十年前，精神分裂症（SCZ）基因组学取得了前所未有的进步。可靠的发现，现在有约 270 个基因座符合显着性和复制的共识标准。观察到其他复杂的精神疾病，所识别的区域绝大多数是非编码的，强烈表明基因调控元件的遗传变异是主要的机制贡献者。由于能力方面存在根本性差距，无法进一步研究这些监管机制。识别、表征和量化与大脑相关的调节元件，但对如何调节元件的理解有限这些元素内的遗传变异会影响它们的功能。为了解决这一知识差距，该项目将全面识别、表征、量化和验证神经元细胞中的非编码功能性非编码调节元件和变体。该提议认为，非编码变异通过直接改变功能而导致精神疾病拟议研究的动机是确定大脑中的调节元件。精神疾病的机制有可能转化为改进的诊断和治疗。由在精神疾病、功能基因组学方面拥有强大跨学科专业知识的团队提供支持，技术发展和统计遗传学，该假设将通过完成三个具体的测试来检验目标：1）全面整合不同数据类型，生成“连接”的假设针对特定基因的精神病学遗传学结果；2) 进行高通量 CRISPR 表观基因组编辑在自然生物学背景下进行筛选以测试目标 1 假设；3) 发展机械理解和使用 TF 结合测定和 SCZ 的 iPS 衍生神经元验证功能性非编码 SCZ 风险变异具有高遗传风险评分的病例。我们的方法是创新的，因为它使用了一组高度互补和多样化的实验推动对 SCZ 相关监管机制进行有针对性的遗传和功能研究的方法。在此过程中，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了复杂的人类表型。