Convergent Genetic and Genomic Analyses of Bipolar Disorder

描述(由申请人提供)： 目的：识别增加双相情感障碍(BP)风险的常见和罕见的基因变异。具体目的：1.利用第二代短读DNA测序仪对来自NIMH基因组计划的6个最高密度的PIC家系和36个最高密度的家系(共42例患者)的1个患病个体的全基因组进行测序，以发现罕见和常见的BP风险变异。2.结合生物信息学标准对在SO1中发现的有害变异累积最多的基因进行排序。我们将实施一种算法，根据功能变化和其他特征(例如外显子和启动子区域，以及微RNA和转录因子结合位点)对变体进行优先排序。这将分两步完成：a.首先，针对在受试者家族中与BP相关的区域发现的变异，然后，b.在基因组的其余部分。3.用长链聚合酶链式反应和第二代短链DNA测序仪对500例病例和500例正常对照进行基因组分割，测定最有希望的5个基因的全序列。4.将新的变异归因于几个大型BP Gwas数据集。目前，这只包括精神病学GWAS联合会(PGC，7,481例和9,250名对照)。基因组精神病学队列和VA CSP#572样本预计也将推出。注：这一步骤不涉及新的实验室工作或临床评估，但届时将只使用现有的GWAs标记数据。背景：双相情感障碍是美国退伍军人和世界范围内致残的主要原因。然而，在VA系统中，对BP的遗传学研究很少。一些全基因组关联研究已经报道了几个新的BP风险基因，但仍然只解释了一小部分遗传风险。全基因组测序是在过去的2-3年里出现的最全面的检测遗传变异的方法，最近在几种疾病中发现了一些新的病因。虽然就在几年前成本还高得令人望而却步，但下一代测序技术现在已经使全基因组测序成为可能，目前它正被应用于复杂的疾病，如精神疾病。建议的方法：我们计划使用Illumina HiSeq 2000对42名BP患者的全基因组进行测序。为了最大限度地增加识别致病变异的机会，这些受试者将来自至少有3个受影响兄弟姐妹的家庭。我们将把这些受试者的基因组序列与公开提供的1000基因组计划中的序列数据进行比较。我们将根据它们的功能对发现的序列变体进行优先排序。根据我们的初步数据，我们预计会发现数千种有害的变种，这些变种不会在现有的数据库中记录下来，例如数据库SNP。利用长片段聚合酶链式反应对500例患者和500名对照的5个有害变异水平最高的基因进行测序。最后，我们将尝试归因于我们在几个现有的大型GWAS数据集中发现的变体，包括目前正在全国范围内收集的VA系统中的一个。

DESCRIPTION (provided by applicant): Objective: To identify common and rare genetic variants which increase the risk of bipolar disorder (BP). Specific Objectives: 1. To discover both rare and common risk variants for BP by sequencing the whole genome of one affected individual from the 6 highest-density PIC families and the 36 highest-density families from the NIMH Genomics Initiative (42 patients in total), at ~32X coverage using second-generation short read DNA sequencers. 2. To rank the genes with greatest accumulations of deleterious variants discovered in SO 1 using a combination of bioinformatics criteria. We will implement an algorithm which prioritizes variants on the basis of functional changes and other features (e.g. exonic and promoter regions, and micro-RNA and transcription factor binding sites). This will be done in two steps: a. First, for variants discovered in regions linked to BP in that subject's family, and then b. In the rest of the genome. 3. Determine the complete DNA sequence of the 5 most promising genes in 500 BP cases and 500 normal controls by genome partitioning with Long PCR and second-generation short read DNA sequencers. 4. Impute novel variation into several large BP GWAS datasets. Currently, this only includes the Psychiatric GWAS Consortium (PGC, 7,481 cases and 9,250 controls). The Genomic Psychiatry Cohort and VA CSP#572 samples are also projected to be available. NB: This step will involve no new laboratory work or clinical assessments, but will only use existing GWAS marker data at that time. Background: Bipolar disorder is a major cause of disability amongst US veterans as well as worldwide. However, very little research in the genetics of BP has been done in the VA system. A number of genomewide association studies have reported several novel risk genes for BP but still explain only a small proportion of the genetic risk. Whole-genome sequencing has emerged in the last 2-3 years as the most comprehensive method to detecting genetic variation, and has recently resulted in several published findings of novel causes in several disorders. While prohibitively expensive only a few years ago, next-generation sequencing technologies have now made whole-genome sequencing possible, and it is currently being applied to complex diseases such as psychiatric illnesses. Proposed Methods: We plan to sequence the whole genomes of 42 patients with BP using the Illumina HiSeq 2000. To maximize the chance of identifying causative variants, these subjects will come from families in which there are at least 3 affected siblings. We will compare the genome sequences of these subjects to the sequence data in the 1000 Genomes Project, which is publicly available. We will prioritize sequence variants discovered based on their function. Based on our preliminary data, we expect to find thousands of deleterious variants which will not have been documented in established databases such as dbSNP. The 5 genes with the highest levels of deleterious variation will be sequenced in 500 cases and 500 controls using long PCR. Finally, we will attempt to impute the variants we discover in several large existing GWAS datasets, including one currently being collected in the VA system nationwide.