Investigating tandem repeat variation as a cause of Alzheimer's disease from exome sequencing data

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 已经在阿尔茨海默病和某些类型的痴呆症患者中被发现。除了空头的扩展之外 串联重复(基序大小在1到6个碱基对之间的重复)，较大重复的拷贝数变化 随着基序的≥20bp，也被称为可变数量的串联重复(VNTRs)，最近被连接到 AD的风险。然而，尽管有证据表明串联重复序列(TR)的变异可以作为 在一些阿尔茨海默病和痴呆症病例中的致病突变，AD队列中没有一致的努力来 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；20,0000 由阿尔茨海默病测序项目产生的外显子，可供社区使用，以及 将使用这些数据来调查两个假设： 1.我们假设某些AD病例是由罕见的高渗透性致病树引起的。vbl.使用 新的生物信息学工具可以识别TRE，我们将搜索仅在AD中观察到的稀有TRE 样本，或者与对照组相比在AD病例中显示显著丰富的样本，因此很可能 导致阿尔茨海默病。然后，将通过聚合酶链式反应或长读测序来验证潜在的致病TRES 可获得的DNA样本。 2.我们假设VNTRs常见的多态拷贝数变异可以作为遗传风险 AD的影响因素。我们开发了一种新的基于读取深度的方法来估计副本数量 来自外显子组测序数据的VNTRs。我们将分析来自9,226个零星AD的可用WES数据 样本和10,151个无关对照，产生了约4,100个基因VNR的拷贝数估计 在WES中表示，它将被用来执行VNTR拷贝数与 病例中的AD状态：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 AD代表了一个合乎逻辑的步骤，它很有可能发现AD的新遗传原因。

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 AD and certain types of dementia. 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 ≥20bp, also known as Variable Number of Tandem Repeats (VNTRs), has recently been linked to risk of AD. However, despite this evidence that variation in tandem repeat (TR) sequences can act as the causative mutations in some cases of AD and dementia, there have been no concerted efforts in AD 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 >20,0000 exomes generated by the Alzheimer's Disease Sequencing Project that are available to the community, and will use these data to investigate two hypotheses: 1. We hypothesize that some cases of AD are caused by rare, highly penetrant pathogenic TREs. Using novel bioinformatic tools that can identify TREs, we will search for rare TREs that are observed only in AD samples, or which show significant enrichment in AD cases compared to controls, and thus are likely causative for AD. Potentially pathogenic TREs will then be validated by PCR or long-read sequencing in available DNA samples. 2. We hypothesize that common polymorphic copy number variation of VNTRs can act as genetic risk factors for AD. 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 9,226 sporadic AD samples and 10,151 unrelated 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 AD 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 AD represents a logical step that has a high likelihood of uncovering novel genetic causes of AD.