Whole Genome Sequencing in Irish Multiplex Schizophrenia Families

项目摘要：虽然多重精神分裂症家系的受影响成员有 与单胎病例相比，复发风险显著升高，平均多基因风险 这些群体之间的得分没有差异，这表明这种较高的家族性的一个来源， 复发风险罕见，影响变异较大。我们将收集全基因组序列（WGS） 从多重精神分裂症家系的600名受影响成员中， 受影响的个人在谱系内和之间可能占增加 复发风险，并减少正在考虑的“变异空间”。在QC之后， 现有的管道，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，目前生产中有30 X外显子组序列数据，和B） 外显子组外的变异将被归算到3600名爱尔兰单身精神分裂症或双相情感障碍患者中， 疾病病例和3000爱尔兰人口对照与GWAS框架数据; 3781额外 配有10 X WGS的UK 10 K质控品可用于提高分析能力。该插补数据集 将使用最近开发的基于核的变异检验方法进行分析 在一个定义的间隔（如基因），避免膨胀的类型1错误。我们使用多个 基因组信息的来源，以开发基因组中每个位置的权重（索引 该位点的变化具有功能后果的先验概率）和检测到的每个变体 （索引观察到的变化具有功能后果的概率），我们建议 以多种方式改进用于该加权的现有基因组信息源。在 aim 3，aim 2a/2b的优先变体将在病例/对照样本中直接进行基因分型 通过定制的微阵列;个体基因或基因组在病例中显示出变异的富集（如果 观察到任何）将在病例/对照样品中重新测序。在目标4中， 将使用标准方法分析来自aim 3的评估的基因型和序列数据， 鉴定个体相关变体和变体富集基因、基因组或其他功能性 序列的我们试图明确识别1）个体变异，这些变异明显更多 常见的情况下，或2）个别基因或其他功能序列或3）基因或功能 序列集因病例中的变异而丰富，以提供有关大脑的关键信息 精神分裂症中干扰的系统，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.