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

 描述（由申请人提供）：最近GWAS对精神疾病的发现能力的增加导致了对精神分裂症（SZ）无可争议的遗传基础的认识。然而，绝大多数这些基因座的机制基础仍然是未知的，阻碍了将遗传发现转化为新的药物靶点和开发SZ患者新疗法的能力。在该提案中，我们克服了这些挑战，并通过结合计算和实验方法，整合系统水平的信息以优先考虑单个基因和基因座，并在源自iPS细胞的10个神经元和3个神经胶质细胞类型中验证其基因调控和细胞效应，来寻求鉴定和表征新型SZ驱动基因和因果变体。目标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，并使用它们来预测精神分裂症驱动基因，基于它们在共同网络/模块中的聚类，以及它们与精神分裂症相关基因座的联系，使用活性相关性，染色质构象和eQTL。目标二：我们搜索增强子区域的精神分裂症富集模块，通过对大脑区域，发育阶段和个体的H3 K27 ac活动的聚类模式发现，使用迭代概率框架联合预测因果驱动基因，变体和监管机构。目标3：我们实验验证了预测的精神分裂症驱动基因和变体在神经元和神经胶质细胞系中的基因调控和神经元/神经胶质细胞表型，这是基于对与800个推定的驱动基因和10，000个推定的因果变体重叠的杂合基因座的靶向测序，以及在敲低和敲除200个候选基因和双向CRISPR后对神经元和神经胶质表型的系统分析-Cas9编辑50个候选因果变体。如果成功，这项雄心勃勃的计划有可能揭示数十种与精神分裂症相关的新靶基因和变异，并为治疗开发开辟新的途径，从而减轻我们一生中精神分裂症的个人和社会负担。

 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.