Investigating tandem repeat expansions as a cause of schizophrenia

串联重复扩增 (TRE)，最常见的是三联体重复，例如聚 (CAG)，已知 是超过 30 种不同的人类神经系统疾病的根源。虽然迄今为止确定的大多数 TRE 均已 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，TRE 已在精神分裂症患者中发现。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），基序 ≥10bp 的较大重复序列的拷贝数变异， 称为可变串联重复序列数（VNTR），最近被认为与精神分裂症风险有关。 然而，尽管有证据表明串联重复（TR）序列的变异可以作为致病因素 某些精神分裂症病例中存在突变，但精神分裂症队列中尚未做出一致努力来 系统地筛选新的 TRE，或者对 VNTR 拷贝数进行基因分型。 新开发的生物信息学方法可用于分析全外显子组测序 (WES) 数据现在提供了填补这一知识空白的机会。利用专业知识和知识 我们已经在其他大型数据集上取得了进展，我们建议应用这些方法来分析 >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. 我们假设某些精神分裂症病例是由罕见的、高渗透性的致病菌引起的 TRE。使用可以识别 TRE 的新型生物信息学工具，我们将搜索以下稀有 TRE：(i) 使用 三重奏设计，在精神分裂症病例中作为从头突变发生，或 (ii) 使用病例：对照设计，发生 与对照相比，在精神分裂症病例中独特或表现出显着富集，因此 可能是精神分裂症的病因。 2. 我们假设VNTR的常见多态性拷贝数变异可以作为遗传风险 精神分裂症的因素。我们开发了一种基于阅读深度来估计副本的新颖方法 来自外显子组测序数据的 VNTR 数量。我们将分析 6,135 个可用的 WES 数据 不相关的精神分裂症病例和 6,245 个种族匹配的对照，生成拷贝数估计 WES 中代表的约 4,100 个基因 VNTR，将用于执行关联分析 病例对照研究中 VNTR 拷贝数与精神分裂症状态的关系。 鉴于 TRE 和 VNTR 中的多态性变异，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，我们相信 TR 变异的研究 精神分裂症代表了一个合乎逻辑的步骤，很有可能揭示精神分裂症的新遗传原因 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.