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：
10377555
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/10377555
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 Complex Consensus DNA Data Development Diagnosis Diagnostic 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 Mental disorders Motivation Mutation Neurons Non-Insulin-Dependent Diabetes Mellitus Organoids Pathway interactions Patients Pattern Pharmacology 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 magnetic resonance imaging 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 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.

项目摘要精神分裂症（SCZ）基因组学已经取得了前所未有的进步。十年前，可能有一个扎实的发现，现在有〜270个基因座符合共识标准以实现重要性和复制。作为在其他复杂的精神病患者中观察到，确定的区域绝大多数是非编码的，强烈表明基因调节元件的遗传变异是主要的机械贡献者。对这些调节机制的进一步研究被基本差距排除在外的能力。识别，表征和量化与大脑相关的调节元素，并有限了解如何这些元素内的遗传变异会影响其功能。为了解决这个知识差距，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不编码调节元件和变体。中心假设建议是非编码变化通过直接改变的功能来促进精神疾病大脑中的调节元素。拟议研究的动机是确定调节性精神疾病的机制有可能转化为改进的诊断和治疗。由一个具有强大跨学科专业知识的团队，功能性基因组学，功能性基因组学专业知识技术开发和统计遗传学，该假设将通过完成三个特定的特定来检验目的：1）潜水员数据类型的全面整合以生成“连接”的假设特定基因的精神遗传结果； 2）执行高通量CRISPR表观组编辑在自然生物学背景下测试目标1个假设的筛选； 3）发展机械理解和使用TF结合测定和IPS衍生的SCZ验证功能性非编码SCZ风险变体遗传风险评分高的病例。我们的方法具有创新性，因为它使用了高度完整且多样化的实验集将有针对性的遗传和功能投资推向与SCZ相关的调节机制的方法。为此，拟议的研究提供了一条急需的途径，以了解不编码变异有助于复杂的人类表型。