Identifying Alzheimer's disease genes using genomic and family data

描述（由申请人提供）：K99/R00独立之路奖的目标是：1)教Marchani博士如何在特定感兴趣的基因组区域内识别影响阿尔茨海默病发病年龄的遗传变异，以便她可以；2)开发一个独立的研究项目，优先考虑其他感兴趣的基因组区域，并在其他数据集中发现其他此类遗传变异。马尔卡尼博士的研究生教育使她具备了探测人口结构、测量遗传多样性以及构建和检验解释这种差异的假设的能力。作为博士后，她最近发表的证据表明，除了APP、PSEN1、PSEN2和APOE外，还有几个基因影响阿尔茨海默病。她有能力找到可能携带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基因变异实际上是负责的。在该奖项的指导K99阶段，她和她的导师将1)通过高分辨率制图来完善这些感兴趣的区域，2)通过DNA重测序缩小的区域来识别候选遗传变异。在该奖项的独立R00阶段，Marchani博士将验证所发现的变异（以及它们所修饰的基因）对阿尔茨海默病发病年龄变化的影响，并撰写并提交一份新的资助申请，以进一步研究这些基因。阿尔茨海默病（AD）具有很强的遗传基础，这是公认的。APP、PSEN1和PSEN2基因的罕见突变导致早发性AD (EOAD)， APOE的常见变异有助于早发性和晚发性AD （LOAD）的风险和发病年龄（AAO）。除APOE外，很难确定与LOAD相关的基因。然而，在多个独立的基于家系的样本中，少数基因组区域提供了与LOAD关联的一致证据，包括我们在一个独特队列中确定的三个区域。鉴于目前对复杂性状的理解，这些区域可能包含有罕见或不常见等位基因的基因或控制区，这些等位基因对外显率和发病年龄有相当大的影响。本提案的目标是应用新的分析和下一代测序技术来发现这些基因或控制区中的一些。华盛顿大学（UW） AD收集包含一个具有独特历史背景的大家族队列和AD AAO的有力证据，这些证据在多个样本中有强有力的联系证据。支持这些地区的其他可用样本包括NIMH和NIA LOAD样本中的队列。我们将使用这些收集的样本，再加上基因组重测序，以确定潜在的发病年龄变异。我们将使用密集SNP基因型UW样品来细化感兴趣的区域。在这些缩小的区域中至少一个，我们将使用靶向DNA测序来确定候选基因/区域。最后，我们将在其他样本收集中对最有希望的发现进行直接基因分型、功能研究和/或基因分型研究。鉴定具有修饰AD AAO变异的新基因将是了解AD生物学的重要一步。检查与发现的基因或控制区有关的分子途径可能会导致额外的治疗靶点。此外，本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异的方法的重要信息，这将有助于设计复杂性状研究。

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.