Investigating tandem repeat expansions as a cause of schizophrenia

串联重复序列扩展(TRE)，最常见的三联体重复序列，如聚(CAG)，已知 30种不同的人类神经疾病的基础。虽然到目前为止确定的大多数TRE是 发现于迟发性神经退行性疾病，如遗传性共济失调和亨廷顿病 已经在精神分裂症患者身上被发现。除了短串联重复序列的扩展(那些 基序大小在1到6个碱基对之间)，带有基序≥10bp的较大重复的拷贝数变异，还 被称为可变数量的串联重复序列(VNTRs)，最近被认为与精神分裂症的风险有关。 然而，尽管有证据表明串联重复序列(TR)的变异可以起到致病作用 在一些精神分裂症病例中，没有精神分裂症队列中的协同努力来 要么系统地筛选新的tre，要么对vntr拷贝数进行分型。 新开发的可用于分析整个外显子组测序的生物信息学方法 (WES)数据现在提供了填补这一知识缺口的机会。利用专业技术和知识 我们已经在其他大型数据集上工作，我们建议将这些方法应用于分析&gt；20,000 可供社区使用的外显子组，并将使用这些数据来研究两个假设： 1.我们假设一些精神分裂症病例是由罕见的、高度渗透的病原体引起的 三叉树。使用可以识别TRE的新型生物信息学工具，我们将搜索稀有的TRE：(I)使用 三重设计，在精神分裂症病例中发生从头突变，或(Ii)使用病例：对照设计，发生 与对照组相比，精神分裂症病例中独特的或显示出显著丰富的，因此 很可能是精神分裂症的病因。 2.我们假设VNTRs常见的多态拷贝数变异可以作为遗传风险 导致精神分裂症的因素。我们开发了一种基于阅读深度的新方法来估计副本 外显子组测序数据中的VNR数目。我们将分析6,135个可用的WES数据 无关的精神分裂症病例和6,245名种族匹配的对照，产生了拷贝数估计 对于WES中表示的~4,100个基因VNR，将用于执行关联分析 1例精神分裂症患者的vntr基因拷贝数对照研究 鉴于TRES和VNTRs的多态变异，两者都代表了已建立的突变机制 导致多种迟发性神经退行性疾病，我们认为在 精神分裂症代表着一个合乎逻辑的步骤，它很有可能发现新的遗传原因 精神分裂症。

Tandem Repeat Expansions (TREs), most commonly of triplet repeats such as poly(CAG), are known to underlie >30 different human neurological diseases. While the majority of TREs identified to date have been found in late-onset neuro-degenerative disorders such as hereditary ataxias and Huntington disease, TREs have been identified in patients with schizophrenia. In addition to expansions of short tandem repeats (those with motif sizes between 1 and 6 base pairs), copy number variation of larger repeats with motifs ≥10bp, also known as Variable Number of Tandem Repeats (VNTRs), has recently been linked to schizophrenia risk. However, despite this evidence that variation in tandem repeat (TR) sequences can act as the causative mutations in some cases of schizophrenia, there have been no concerted efforts in schizophrenia cohorts to either systematically screen for novel TREs, or to genotype VNTR copy numbers. Newly developed bioinformatic approaches that can be applied to analyze Whole Exome Sequencing (WES) data now provide an opportunity to fill this knowledge gap. Utilizing the expertise and knowledge that we have gained working on other large datasets, we propose to apply these approaches to analyze >20,000 exomes that are available to the community, and will use these data to investigate two hypotheses: 1. We hypothesize that some cases of schizophrenia are caused by rare, highly penetrant pathogenic TREs. Using novel bioinformatic tools that can identify TREs, we will search for rare TREs that (i) using a trio design, occur as de novo mutations in schizophrenia cases, or (ii) using a case:control design, occur uniquely in or show significant enrichment in schizophrenia cases compared to controls, and thus are likely causative for schizophrenia. 2. We hypothesize that common polymorphic copy number variation of VNTRs can act as genetic risk factors for schizophrenia. We have developed a novel approach based on read depth to estimate copy number of VNTRs from exome sequencing data. We will analyze available WES data from 6,135 unrelated schizophrenia cases and 6,245 ethnically matched controls, generating copy number estimates for ~4,100 genic VNTRs that are represented in WES, which will be used to perform association analysis of VNTR copy number with schizophrenia status in a case:control study. Given that TREs, and polymorphic variation in VNTRs, both represent established mutational mechanisms that contribute to a variety of late-onset neuro-degenerative conditions, we believe that the study of TR variation in schizophrenia represents a logical step that has a high likelihood of uncovering novel genetic causes of schizophrenia.