Whole Genome Sequencing in Irish Multiplex Schizophrenia Families

项目概述：尽管多重精神分裂症家系中受影响的成员有 与单胎病例相比，复发风险显著增加，平均多基因风险 这些组之间的得分没有差异，这表明这种更高的家族成员的一个来源 复发风险较少，影响变异较大。我们将收集全基因组序列(WGS) 从600个多重精神分裂症家系成员中识别罕见的共有变异 由家系内部和家系之间受影响的个体潜在地解释了 复发风险，并减少正在考虑的“变量空间”。在QC之后，并呼叫我们的 现有的流水线，a)外显子组中的家族序列变异将在2000年直接分析爱尔兰 病例和2000个爱尔兰对照，目前生产中的30倍外显子序列数据，以及b) 外显子外的变异将被归因于3600名爱尔兰单身精神分裂症或双相情感障碍患者 障碍病例和3,000个爱尔兰人口控制，使用GWAS框架数据；增加3781个 具有10倍WGS的UK10K控件可用于增强分析能力。此推定的数据集 将使用最新开发的基于内核的变量聚合测试方法进行分析 在定义的间隔(例如基因)上，以避免类型1错误的膨胀。我们使用多个 基因组信息源，以确定基因组中每个位置的权重(索引 站点处的变化具有功能后果的先验概率)，并且检测到每个变体 (索引观察到的变化具有功能后果的概率)，我们建议 以多种方式改进现有的基因组信息源以实现这一权重。在……里面 目标3，来自目标2a/2b的优先变异将在病例/对照样本中直接进行基因分型 通过定制微阵列；单个基因或基因组集在病例中显示变异丰富(如果 任何观察到的)将在病例/对照样本中重新测序。在目标4中，直接 来自目标3的评估的基因类型和序列数据将使用标准方法进行分析 确定单个相关变异，以及变异丰富的基因、基因集或其他功能 序列。我们试图毫不含糊地确定1)显著高于 常见的情况，或2)单个基因或其他功能序列，或3)基因或功能 序列集丰富了案例中的变化，以提供关于大脑的关键信息 精神分裂症的系统受到干扰，以及这些等位基因增加风险的机制。

Project Summary: Although affected members of multiplex schizophrenia pedigrees have substantially elevated recurrence risk compared to singleton cases, the mean polygenic risk scores between these groups do not differ, suggesting that one source of this higher familial recurrence risk is rare, higher impact variation. We will collect whole genome sequence (WGS) from 600 affected members of multiplex schizophrenia pedigrees to identify rare variation shared by affected individuals within and between pedigrees potentially accounting for the increased recurrence risk, and reducing the `variant space' under consideration. After QC and calling in our existing pipeline, a) familial sequence variants in the exome will be directly analyzed in 2000 Irish cases and 2000 Irish controls with 30X exome sequence data in production currently, and b) variants outside the exome will be imputed into 3600 Irish singleton schizophrenia or bipolar disorder cases and 3000 Irish population controls with GWAS framework data; 3781 additional UK10K controls with 10X WGS are available to increase analysis power. This imputed dataset will be analyzed using recently developed methods for kernel-based tests of variation aggregated over a defined interval (such as a gene) that avoid the inflation of type-1 error. We use multiple sources of genomic information to develop weights for each position in the genome (indexing the prior probability that a change at the site has functional consequence) and each variant detected (indexing the probability that observed changes have functional consequence), and we propose to improve the existing genomic information sources for this weighting in a number of ways. In aim 3, prioritized variants from aim 2a/2b will be directly genotyped in the case/control samples by custom microarray; individual genes or genesets showing enrichment of variation in cases (if any are observed) will be resequenced in the case/control sample. In Aim 4, the directly assessed genotypic and sequence data from aim 3 will be analyzed using standard methods to identify individual associated variants, and variant-enriched genes, genesets or other functional sequences. We seek to unambiguously identify 1) individual variants that are significantly more common in cases, or 2) individual genes or other functional sequences or 3) gene- or functional sequence sets enriched for variation in cases to provide critical information about the brain systems perturbed in schizophrenia, and the mechanisms by which such alleles increase risk.