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

 描述(由申请人提供)：最近GWA对精神障碍的发现能力的增加导致了对精神分裂症(SZ)一个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不明确，阻碍了将遗传发现转化为新的药物靶点和为SZ患者开发新治疗方法的能力。在这个方案中，我们克服了这些挑战，试图通过结合计算和实验方法，整合系统水平的信息来确定单个基因和位点的优先顺序，并验证它们在来自iPS细胞的10种神经细胞和3种神经胶质细胞类型中的基因调控和细胞效应，从而识别和表征新的SZ驱动基因和因果变体。目的1：我们利用多个脑区和发育阶段来推断基因共表达网络和模块，并根据它们在常见网络/模块中的聚集性，以及它们与精神分裂症相关基因的联系，利用活动相关性、染色质构象和eQTL来预测精神分裂症驱动基因。目的2：我们使用迭代概率框架联合预测因果驱动基因、变异和调节因子，通过H3K27ac活动跨大脑区域、发育阶段和个体的聚集模式发现增强子区域的精神分裂症丰富模块。目的：我们通过对重叠的800个可能的驱动基因和10,000个可能的因果变异的杂合基因座的定向测序，以及200个候选基因被敲除和敲除后的神经元和神经胶质细胞表型的系统描述，以及50个候选因果变异的双向CRISPR-Cas9编辑，从实验上验证了预测的精神分裂症驱动基因和变异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。如果成功，这项雄心勃勃的计划有可能揭示数十个与精神分裂症相关的新目标基因和变种，并为治疗开发开辟新的途径，可能会减轻精神分裂症在我们一生中的个人和社会负担。

 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.