Identifying Alzheimer's disease genes using genomic and family data

项目摘要/摘要 K99/R00独立之路奖的目标是1)教Marchani博士如何识别 在特定的感兴趣基因组区域内影响阿尔茨海默病发病年龄的基因变异，因此 她可以，2)开发一个独立的研究计划，优先考虑其他感兴趣的基因组区域和 在其他数据集中发现其他类似的遗传变异。马尔查尼博士的研究生教育为她奠定了基础 能够检测种群结构、测量遗传多样性以及构建和测试假设以解释 这种变种。作为一名博士后研究员，她最近发表了一些证据，除了 APP、PSEN1、PSEN2和APOE影响阿尔茨海默病。她有能力找到可能的基因组区域 存在影响阿尔茨海默病风险的变异，但需要额外的培训来确定哪些 事实上，基因变异是造成这一现象的原因。在这个奖项的指导K99阶段，她和她的导师将 1)通过高分辨率作图来精炼这些感兴趣的区域，以及2)通过以下方式识别候选遗传变异 对狭窄的区域进行DNA重新测序。在该奖项的独立R00阶段，Marchani博士将 验证已发现的变异(及其修饰的基因)对年龄-年龄差异的影响 阿尔茨海默氏症的发病，并撰写并提交一份新的拨款提案，以进一步询问这些基因。 众所周知，阿尔茨海默病(AD)有很强的遗传基础。这款应用程序中罕见的突变， PSEN1和PSEN2基因导致早发性阿尔茨海默病(EOAD)，APOE的常见变异导致风险 早发和晚发AD(LOAD)的发病年龄(AAO)。除了APOE，很难做到 确定与负载相关的基因。然而，少数基因组区域提供了一致的 包括三个地区在内的多个基于家系的独立样本与负荷相关的证据 这是我们在一个独特的队列中发现的。鉴于目前对复杂特征的理解，很可能是这些 区域包含具有稀有或不常见等位基因的基因或控制区，这些基因或控制区对 外显率和发病年龄。这项提议的目标是应用新的分析型和下一代 测序技术，以找到其中的一些基因或控制区。 华盛顿大学(UW)的AD收藏包含了一群大家庭，这是一种独特的历史 AD AAO的背景和强有力的证据，在多个样本中有强烈的连锁证据的地区。 也支持这些相同地区的其他可用样本包括NIMH和NIA中的一个队列 加载样本。我们将使用这些收集的样本，再加上基因组重新测序，来鉴定 潜在的发病年龄变异。我们将使用UW样本的密集SNP基因型来精炼 利息。在至少一个狭窄的区域内，我们将使用定向DNA测序来识别 候选基因/区域。最后，我们将通过直接基因分型来跟进最有希望的发现， 功能研究，和/或其他样本收集中的基因分型对象。 鉴定具有修饰AD AAO的变体的新基因将是迈向 了解AD生物学。基因或控制区所涉及的分子通路的检测 这一发现可能会带来更多的治疗靶点。此外，这项研究将提供重要的 关于阿尔茨海默病的遗传结构和识别相关风险变异的方法的信息， 这将对复杂性状研究的设计有所帮助。

Project Summary/Abstract The goals of this K99/R00 Pathway to Independence award are to 1) teach Dr. Marchani how to identify genetic variants influencing age-at-onset of Alzheimer's disease within a specific genomic region of interest, so that she may, 2) develop an independent research program to prioritize other genomic regions of interest and discover other such genetic variants in other data sets. Dr. Marchani's graduate education established her ability to detect population structure, measure genetic diversity and construct and test hypotheses to explain that variation. As a postdoctoral fellow, she has recently published evidence that several genes in addition to APP, PSEN1, PSEN2, and APOE influence Alzheimer's disease. She has the skills to find genomic regions likely to harbor variants influencing Alzheimer's disease risk, but requires additional training to determine which genetic variants are in fact responsible. During the mentored K99 phase of this award, she and her mentors will 1) refine these regions of interest by high-resolution mapping, and 2) identify candidate genetic variants by DNA resequencing the narrowed regions. During the independent R00 phase of this award, Dr. Marchani will validate the contribution of the discovered variants (and the genes they modify) influence variation in age-at- onset of Alzheimer's disease, and write and submit a new grant proposal to further interrogate those genes. It is well-established that Alzheimer disease (AD) has a strong genetic basis. Rare mutations in the APP, PSEN1 and PSEN2 genes lead to early onset AD (EOAD), and common variation in APOE contributes to risk and age-at-onset (AAO) in both early and late onset AD (LOAD). Other than APOE, it has been difficult to identify relevant genes for LOAD. However, a small number of genomic regions have provided consistent evidence for linkage with LOAD across multiple independent pedigree-based samples, including three regions that we identified in a unique cohort. Given the current understanding of complex traits, it is likely these regions harbor genes or control regions with rare or uncommon alleles that have considerable effects on penetrance and age-at-onset. The goal of this proposal is to apply novel analytic and next generation sequencing technologies to find some of these genes or control regions. The University of Washington (UW) AD collection contains a cohort of large families a unique historical background and strong evidence for AD AAO in regions with strong evidence of linkage in multiple samples. Additional available samples that also support these same regions include a cohort within the NIMH and NIA LOAD samples. We will use samples from these collections, coupled with genomic resequencing, to identify the underlying age-at-onset variants. We will use dense SNP genotypes for UW samples to refine the regions of interest. Within at least one of these narrowed regions, we will use targeted DNA sequencing to identify candidate genes/regions. Finally, we will follow-up the most promising findings with direct genotyping, functional studies, and/or genotyping subjects in other sample collections. The identification of novel genes with variants modifying AD AAO would be a significant step towards understanding AD biology. Examination of molecular pathways implicated by the genes or control regions found will likely lead to additional therapeutic targets. In addition, this study will provide important information about the genetic architecture of AD and approaches to identifying the associated risk variants, which will be useful for design of complex-trait studies.