Genetic Studies of Alzheimer Disease in Koreans

摘要 大多数阿尔茨海默病(AD)的遗传基础是在欧洲血统的高加索人中发现的 (EAS)，并需要10,000至75,000名受试者样本来检测它们。我们和其他人有 证明阿尔茨海默病的风险变异可以在基因更同质性的种族群体中识别出来 背景使用包含数千或更少受试者的样本。对非EA群体的研究也 提供机会发现罕见的变体，或由于修改而在EA中显示较小的效果大小 受其他基因和环境因素的影响。我们将把我们的努力指向韩国人，这是一个人口比例很高的国家 阿尔茨海默病的患病率，但像其他东亚人群一样，没有包括在大型DNA测序中 研究表明，除了与载脂蛋白E有关外，人们对AD的遗传基础知之甚少。他们有 保持了独特的遗传特征，反映了遗传漂变和新的 在过去两千年里的突变。我们将利用韩国人的遗传结构来促进发现 通过研究罕见和常见的遗传变异以及阿尔茨海默病的影响，研究与AD相关的基因和变异。 基因表达的相关变异。为了实现我们的科学目标，我们将研究AD病例和对照 谁被确定并在朝鲜国家痴呆症研究中心进行纵向跟踪 位于大韩民国光州西南部城市的大学，并从每个参与者那里获得 血液样本和表型数据，包括临床检查、人口统计学、病史和生活方式 信息。此外，大多数受试者还将接受广泛的神经心理测试。 特别是针对韩国人和脑部核磁共振扫描。该队列将包括一个无关的2000例AD病例组 以及从现有患者登记和预期确定的受试者中确定的2,000名老年人对照 世卫组织将利用为韩国人设计的微阵列生成可获得的全球气候变化数据。DNA样本来自 所有受试者将进行全基因组测序(WGS)。WGS数据将使用建立的管道进行处理 阿尔茨海默病测序项目。我们将对AD进行全基因组关联研究，使用 基于调整年龄、性别和人口的模型的单一变异和基于基因的测试的方法 下部结构。顶尖发现将在基因组学中心收集的其他种族的数据集中复制 阿尔茨海默病跨种族分析和方法用于阿尔茨海默病测序项目 重点研究影响蛋白质结构、转录和基因表达的变异。接下来，我们将执行一项 研究对象为发病年龄、脑成像和认知内表型。最后，我们将确定基因靶点 通过使用公共数据集执行表达数量性状基因座分析来获得排名靠前的SNPs 包含大脑和其他组织中的基因型和基因表达数据，并建立功能连接 通过通径分析和共表达网络分析，对排名靠前的SNPs和基因进行分析。我们预计 该项目将确定开发新药的新目标，以治疗或延缓导致AD的机制。

ABSTRACT Most discoveries of the genetic basis of Alzheimer disease (AD) were made in Caucasians of European ancestry (EAs) and required samples between 10,000 and 75,000 subjects to detect them. We and others have demonstrated that risk variants for AD can be identified in ethnic groups of a more homogeneous genetic background using samples comprising several thousand or fewer subjects. Studies of non-EA populations also afford the opportunity to discover variants that are rare or display a smaller effect size in EAs due to modification by other genes and environmental factors. We will direct our efforts to Koreans, a population which has a high prevalence of AD, but, like other East Asian populations, have not been included in large DNA sequencing studies and for whom little is known about the genetic basis of AD other than association with APOE. They have maintained a distinct genetic profile that reflects a unique component resulting from genetic drift and new mutations during the last two millennia. We will leverage the genetic architecture of Koreans to promote discovery of AD-related genes and variants by studying rare and common genetic variation, and the impact of AD- associated variants on gene expression. To accomplish our scientific goals, we will study AD cases and controls who are ascertained and followed longitudinally at the National Center for Research on Dementia at Chosun University located in the southwestern city of Gwangju, Republic of Korea, and obtain from each participant a blood specimen and phenotypic data including clinical exam, demographic, medical history and lifestyle information. In addition, most subjects will undergo an extensive neuropsychological test battery developed specifically for Koreans and a brain MRI scan. The cohort will comprise an unrelated group of 2,000 AD cases and 2,000 elderly controls ascertained from existing patient registries and prospectively identified subjects all of whom will have GWAS data available generated using a microarray designed for Koreans. DNA specimens from all subjects will be whole genome sequenced (WGS). WGS data will be processed using pipelines established by the Alzheimer Disease Sequencing Project. We will conduct a genome-wide association study for AD using methods for single variant and gene-based tests based on models that adjust for age, sex and population substructure. Top-findings will be replicated in datasets of other ethnicities assembled by the Genomics Center for Alzheimer Disease for the Alzheimer Disease Sequencing Project using trans-ethnic analysis and approaches that focus on variants affecting protein structure, transcription, and gene expression. Next we will perform a GWAS for age at onset and brain imaging and cognitive endophenotypes. Finally, we will identify gene targets of the top-ranked SNPs by performing expression quantitative trait locus analysis using public datasets containing genotype and gene expression data in brain and other tissues, and establish functional connections among the top-ranked SNPs and genes using pathway analysis and co-expression network analysis. We expect this project will identify novel targets for development of new drugs to treat or retard mechanisms leading to AD.