Investigating tandem repeat expansions as a cause of schizophrenia

已知串联重复序列扩增（Tendem Repeat Expansions，TREs），最常见的是三重重复序列，如多聚（CAG）， 是超过30种人类神经系统疾病的基础。虽然迄今为止确定的大多数TREs都是 在迟发性神经退行性疾病如遗传性共济失调和亨廷顿病中发现， 在精神分裂症患者中被发现。除了短串联重复序列的扩增（那些 基序大小在1 - 6个碱基对之间），基序≥ 10 bp的较大重复序列的拷贝数变异， 称为可变串联重复数（VNTR），最近与精神分裂症风险有关。 然而，尽管有证据表明串联重复序列（TR）的变异可以作为致病因素， 在某些精神分裂症病例中，精神分裂症队列中没有一致的努力， 或者系统地筛选新的TREs，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， 我们已经获得了其他大型数据集的工作，我们建议应用这些方法来分析> 20，000 exomes是可用的社区，并将使用这些数据来调查两个假设： 1.我们假设一些精神分裂症病例是由罕见的，高度渗透的致病性， TREs。使用可以识别TREs的新的生物信息学工具，我们将搜索罕见的TREs，（i）使用 三重设计，在精神分裂症病例中作为新生突变发生，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地或显示出显著的富集，因此， 可能导致精神分裂症 2.我们假设VNTR的常见多态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的新方法来估计拷贝 来自外显子组测序数据的VNTR数目。我们将分析来自6，135个国家的可用WES数据， 无关的精神分裂症病例和6，245名种族匹配的对照， 对于WES中表示的约4，100个基因VNTR，其将用于执行关联分析 VNTR拷贝数与精神分裂症状态的关系：对照研究。 鉴于TREs和VNTR中的多态性变异，两者都代表了已建立的突变机制， 有助于各种迟发性神经退行性疾病，我们认为，TR变异的研究， 精神分裂症代表了一个逻辑步骤，有很高的可能性发现新的遗传原因， 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.