Identifying Alzheimer's disease genes using genomic and family data

项目总结/摘要 这个K99/R 00独立之路奖的目标是：1）教Marchani博士如何识别 在特定的感兴趣的基因组区域内影响阿尔茨海默病发病年龄的遗传变异， 她可能，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， 在其他数据集中发现其他这样的遗传变异。马查尼博士的研究生教育使她 能够检测种群结构，测量遗传多样性，构建和测试假设，以解释 这种变化。作为一名博士后研究员，她最近发表的证据表明，除了基因， APP，PSEN 1，PSEN 2和APOE影响阿尔茨海默病她有能力找到基因组区域 携带影响阿尔茨海默病风险的变异，但需要额外的训练来确定 事实上，基因变异是罪魁祸首。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细化这些感兴趣的区域，以及2）通过以下方式来识别候选遗传变异： DNA重新测序缩小的区域。在该奖项的独立R 00阶段，Marchani博士将 验证发现的变异（及其修饰的基因）对年龄变化的影响， 阿尔茨海默病的发病，并撰写和提交一份新的拨款申请，以进一步询问这些基因。 众所周知，阿尔茨海默病（AD）具有很强的遗传基础。APP中的罕见突变， PSEN 1和PSEN 2基因导致早发性AD（EOAD），APOE的常见变异有助于风险 在早期和晚期AD（LOAD）中，除了APOE， 识别与负载相关的基因。然而，少数基因组区域提供了一致的 在多个独立的基于谱系的样本中，包括三个地区，有证据表明与LOAD存在关联 我们在一个独特的群体中发现的。鉴于目前对复杂特征的理解， 区域含有基因或控制区域，其具有对人类具有相当大影响的罕见或不常见等位基因。 发病年龄和昏迷程度该提案的目标是应用新的分析和下一代 测序技术来找到这些基因或控制区域。 华盛顿大学（UW）AD收藏了一批大家庭， 背景和强有力的证据表明，在多个样本中存在强有力的连锁证据的地区存在AD AAO。 支持这些相同地区的其他可用样本包括NIMH和NIA内的队列 加载样品。我们将使用这些样本，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UW样本的密集SNP基因型来细化 兴趣在这些缩小的区域中的至少一个区域内，我们将使用靶向DNA测序来识别 候选基因/区域。最后，我们将对最有希望的发现进行直接基因分型， 功能研究和/或在其他样品收集中对受试者进行基因分型。 鉴定具有修饰AD AAO的变体的新基因将是实现基因工程的重要一步。 了解AD生物学检查基因或控制区所涉及的分子途径 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AD遗传结构的信息和识别相关风险变体的方法， 这将有助于复杂性状研究的设计。

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.