Identifying Alzheimer's disease genes using genomic and family data

描述(申请人提供)：这项K99/R00独立之路奖的目标是1)教Marchani博士如何在感兴趣的特定基因组区域内识别影响阿尔茨海默病发病年龄的基因变异，以便她可以，2)开发独立的研究计划，以确定其他感兴趣的基因组区域的优先顺序，并在其他数据集中发现其他此类基因变异。马尔查尼博士的研究生教育确立了她检测种群结构、测量遗传多样性以及构建和测试解释这种变异的假设的能力。作为一名博士后，她最近发表了一些证据，表明除了APP、PSEN1、PSEN2和APOE之外，还有几个基因会影响阿尔茨海默病。她有能力找到可能含有影响阿尔茨海默病风险的变异的基因组区域，但需要额外的培训来确定哪些遗传变异实际上是相关的。在该奖项的指导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)通过对缩小的区域进行DNA重新测序来识别候选基因变异。在该奖项的独立R00阶段，Marchani博士将验证已发现的变异(及其修改的基因)对阿尔茨海默病发病年龄变异的影响，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。APP、PSEN1和PSEN2基因的罕见突变导致早发性AD(EOAD)，APOE的常见变异导致早发性和晚发性AD(LOAD)的风险和发病年龄(AAO)。除载脂蛋白E外，很难确定与LOAD相关的基因。然而，少数基因组区域为多个独立的家系样本提供了与LOAD连锁的一致证据，包括我们在一个独特的队列中确定的三个区域。鉴于目前对复杂性状的理解，这些区域很可能含有基因或具有罕见或不常见等位基因的控制区，这些基因或控制区对外显性和发病年龄有相当大的影响。这项提议的目标是应用新的分析和下一代测序技术来寻找其中的一些基因或控制区。华盛顿大学(UW)的AD收集包含了一个大家族队列，一个独特的历史背景和强有力的证据表明，在多个样本中存在强烈联系的地区的AD AAO。也支持这些相同区域的其他可用样本包括NIMH和NIA负载样本中的一个队列。我们将使用来自这些收集的样本，结合基因组重测序，来识别潜在的发病年龄变异。我们将使用UW样本的密集SNP基因型来提炼感兴趣的区域。在这些缩小的区域中，至少有一个区域，我们将使用定向DNA测序来确定候选基因/区域。最后，我们将通过直接基因分型、功能研究和/或其他样本收集中的基因分型对象来跟进最有希望的发现。识别新的基因及其变异体修饰AD AAO将是理解AD生物学的重要步骤。对所发现的基因或控制区所涉及的分子通路的检查可能会导致更多的治疗靶点。此外，这项研究将提供有关阿尔茨海默病的遗传结构和识别相关风险变量的方法的重要信息，这将有助于复杂性状研究的设计。

DESCRIPTION (provided by applicant): 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.