Network-based prediction and validation of causal schizophrenia genes and variants

基于网络的精神分裂症致病基因和变异的预测和验证

基本信息

批准号：
9108677
负责人：
Mark Joseph Daly
金额：
$ 42.42万
依托单位：
BROAD INSTITUTE, INC.
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-05-01 至 2021-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9108677
关键词：
Alleles Bayesian Modeling Biological Assay Brain Brain region CRISPR/Cas technology Calcium Candidate Disease Gene Cell Line Cells ChIP-seq Chromatin Communities Computing Methodologies Data Set Development Enhancers Gene Expression Gene Targeting Genes Genetic Haplotypes Hybrids Individual Investments Joints Knock-out Link Maps Mental disorders Methods Modeling Molecular Conformation Network-based Neuroglia Neurons Patients Pattern Phenotype Probability Regulator Genes Resources Schizophrenia Signal Transduction Small Interfering RNA Staging Statistical Models Structure Synapses System Testing Translating Untranslated RNA Validation Variant Work base cell type clinically relevant epigenomics expectation genetic variant genome editing genome wide association study induced pluripotent stem cell knock-down new therapeutic target novel public health relevance risk variant synaptic function targeted sequencing therapeutic development transcriptome sequencing

项目摘要

DESCRIPTION (provided by applicant): The recent increase in GWAS discovery power for psychiatric disorders has led to the recognition of an undisputed genetic basis for schizophrenia (SZ). However, the mechanistic basis of the vast majority of these loci remains uncharacterized, hindering the ability to translate genetic findings into novel drug targets and develop new treatments for SZ patients. In this proposal, we overcome these challenges and seek to identify and characterize novel SZ driver genes and causal variants by combining computational and experimental methods, integrating systems-level information to prioritize individual genes and loci, and validating their gene- regulatory and cellular effects in 10 neuronal and 3 glial cell tyes derived from iPS cells. Aim 1: We infer gene co-expression networks and modules using multiple brain regions and developmental stages, and use them to predict schizophrenia driver genes based on their clustering in common networks/modules, and their linking to schizophrenia-associated loci using activity correlation, chromatin conformation and eQTLs. Aim 2: We search for schizophrenia-enriched modules of enhancer regions, discovered by clustering patterns of H3K27ac activity across brain regions, developmental stages, and individuals, using an iterative probabilistic framework for joint prediction of causal driver genes, variants, and regulators. Aim 3: We experimentally validate the gene- regulatory and neuronal/glial cellular phenotypes of predicted schizophrenia driver genes and variants in neuronal and glial cell lines based on targeted sequencing of heterozygous loci overlapping 800 putative driver genes and 10,000 putative causal variants, and systematic profiling of neuronal and glial phenotypes upon knockdown and knockout of 200 candidate genes and bidirectional CRISPR-Cas9 editing of 50 candidate causal variants. If successful, this ambitious proposal has the potential to reveal dozens of new target genes and variants associated with Schizophrenia, and open up new avenues for therapeutic development that may alleviate the personal and societal burden of schizophrenia in our lifetimes.

描述（由适用提供）：GWAS发现能力的最新增加导致人们认识到精神分裂症（SZ）无可争议的遗传基础。但是，这些基因座绝大多数的机械基础仍然没有表征，从而阻碍将遗传发现转化为新的药物靶标并为SZ患者开发新的治疗方法。在该提案中，我们克服了这些挑战，并试图通过结合计算和实验方法，集成系统级信息以优先级和基因座，并验证其基因调控和细胞在10个神经细胞类型中衍生自IPS细胞中的基因调控和细胞效应，从而确定和表征新颖的SZ驱动基因和因果变异。 AIM 1：我们使用多个大脑区域和发育阶段推断基因共表达网络和模块，并使用它们根据公共网络/模块中的聚类来预测精神分裂症驱动基因，以及它们与精神分裂症相关的LOCI的链接，使用活性相关，染色素构型和EQTL。 AIM 2：我们在跨大脑区域的H3K27AC活性的聚类模式，发展阶段和个体的聚类模式中搜索增强剂区域的精神分裂症模块，使用迭代概率框架，用于结合因果驱动基因，变体和调节剂的关节预测。 Aim 3: We experimentally validate the gene-regulatory and neuronal/glial cellular phenotypes of predicted schizophrenia driver genes and variants in neuronal and glial cell lines based on targeted sequencing of heterozygous loci overlapping 800 putative driver genes and 10,000 putative causal variants, and systematic profiling of neuronal and glial phenotypes upon knockdown and knockout of 200候选基因和双向CRISPR-CAS9编辑50个候选因果变体。如果成功的话，这项雄心勃勃的提议有可能揭示数十种与精神分裂症相关的新靶基因和变体，并为治疗发展开辟了新的途径，以减轻我们一生中精神分裂症的个人和社交伯恩。