Convergent Genetic and Genomic Analyses of Bipolar Disorder

描述（由申请人提供）： 目的：确定增加双相情感障碍（BP）风险的常见和罕见遗传变异。具体目标：1。通过使用第二代短读DNA测序仪对来自NIMH基因组学计划的6个最高密度PIC家族和36个最高密度家族（共42名患者）的1名受影响个体的全基因组进行测序，以~ 32 X覆盖率发现BP的罕见和常见风险变体。2.使用生物信息学标准的组合对SO 1中发现的有害变体累积最多的基因进行排名。我们将实现一种算法，该算法根据功能变化和其他特征（例如外显子和启动子区域，以及微小RNA和转录因子结合位点）对变体进行优先排序。这将通过两个步骤完成：a.首先，在该受试者家族中与BP相关的区域中发现的变异，然后是B。在基因组的其余部分。3.采用长片段PCR和第二代短片段测序仪对500例BP患者和500例正常对照进行基因组分区，测定5个最有希望的基因的全序列。4.将新的变异输入几个大型BP GWAS数据集。目前，这只包括精神病GWAS联盟（PGC，7，481例和9，250例对照）。基因组精神病学队列和VA CSP#572样本预计也将提供。注：此步骤将不涉及新的实验室工作或临床评估，但届时将仅使用现有的GWAS标记数据。背景：双相情感障碍是美国退伍军人以及全世界残疾的主要原因。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，但仍然只能解释一小部分遗传风险。全基因组测序在过去的2-3年中已经成为检测遗传变异的最全面的方法，并且最近已经导致了几种疾病中新原因的几项已发表的发现。虽然仅在几年前，下一代测序技术还非常昂贵，但现在已经使全基因组测序成为可能，目前正应用于精神疾病等复杂疾病。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。为了最大限度地提高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。我们将这些受试者的基因组序列与1000个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异，这些变异在dbSNP等已建立的数据库中没有记录。将使用长PCR对500例病例和500例对照中具有最高水平有害变异的5个基因进行测序。最后，我们将尝试对我们在几个大型现有GWAS数据集中发现的变体进行估算，其中包括目前在全国VA系统中收集的一个数据集。

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.