Exploring the Genetics of Alzheimer's Disease in Humans and Drosophila

描述（由申请人提供）：基因分型技术和统计方法的进步使得发现常见疾病的易感基因成为现实。目前正在对阿尔茨海默病（AD）进行全基因组关联研究（GWAS），随着识别遗传变异的障碍被克服，可能会出现经过验证的位点。虽然一个主要的障碍是样本量，另一个是表型异质性。由于患者样本的临床异质性和对照组中存在大量的亚临床AD相关病理，AD诊断的离散临床结果受到了影响。定量中间表型的使用是一种补充方法，可以最大限度地减少这些混杂因素，并有可能提高统计能力。我们正在进行一项人类基因组的基因位点分析，这些基因位点与来自社区研究的两个大型尸检队列中的AD神经病理学定量测量相关，宗教秩序研究（ROS）和拉什记忆和衰老项目（MAP）。将对多态性进行二次评估，以确定其与认知能力下降的关联，以确定其临床相关性。我们建议将这些人类遗传学研究与现有的与黑胃果蝇AD相关的遗传模型中一个简单但功能强大的功能筛选结合起来。这一策略将使我们能够有效地从GWAS结果列表转移到易感基因的验证和遗传精细定位的位点选择。具体来说，我们建议执行以下目标：目标1:AD神经病理学中间表型的GWAS。我们将使用来自1000多名受试者的合并尸检队列的906,600个单核苷酸多态性和946,000个拷贝数探针的数据进行全基因组关联分析。将根据淀粉样斑块和神经原纤维缠结的计数，对全球阿尔茨海默病病理进行定量测量。目的2：评估阿尔茨海默病病理易感位点与认知能力下降的关系。GWAS得分最高的多态性将在3800多名受试者的汇总队列中进行评估，并采用纵向神经精神病学测量来确定其临床相关性。该队列将包括ROS和MAP，以及来自以人口为基础的芝加哥健康和老龄化项目的受试者。目的3：在果蝇模型系统中验证候选易感基因。我们将利用果蝇遗传学的高通量能力，以及果蝇基因组接近饱和的功能增益和功能丧失试剂的可用性，筛选目标1和2中鉴定的候选基因，以确定其与Tau神经毒性的功能相互作用。目标4：最具潜力基因座的精细定位。

DESCRIPTION (provided by applicant): Advances in genotyping technology and statistical methods have converged to make the discovery of susceptibility genes for common diseases a reality. Genome-wide association studies (GWAS) are being performed for Alzheimer's disease (AD) and it is likely that validated loci will emerge, as impediments to the identification of genetic variants are overcome. While a major barrier is sample size, another is phenotypic heterogeneity. The discrete clinical outcome of AD diagnosis is burdened by clinical heterogeneity in the patient sample and the presence of substantial but sub-clinical AD-related pathology in control subjects. The use of quantitative intermediate phenotypes is a complementary approach that minimizes these confounders and has the potential to enhance statistical power. We are conducting an analysis of the human genome for loci associated with a quantitative measure of AD neuropathology present in two large autopsy cohorts from community-based studies, the Religious Orders Study (ROS) and the Rush Memory and Aging Project (MAP). Polymorphisms will be secondarily evaluated for associations with cognitive decline to establish their clinical relevance. We propose to couple these human genetic studies with a simple but powerful functional screen in an existing genetic model relevant to AD in Drosophila melanogaster. This strategy will enable us to move efficiently from a list of GWAS results to validation of susceptibility genes and selection of loci for genetic fine mapping. Specifically we propose to execute the following aims: Aim 1: A GWAS for an AD neuropathology intermediate phenotype. We will perform genome-wide association analysis using data on 906,600 single nucleotide polymorphisms and 946,000 copy number probes from a pooled autopsy cohort of more than 1000 subjects. Associations will be examined for a quantitative measure of global AD pathology based on counts of amyloid plaques and neurofibrillary tangles. Aim 2: Evaluation of AD pathology susceptibility loci for associations with cognitive decline. Top-scoring polymorphisms from the GWAS will be evaluated in a pooled cohort of more than 3,800 subjects with longitudinal neuropsychiatric measures to establish their clinical relevance. This cohort will include both ROS and MAP, as well as subjects from the population-based Chicago Health and Aging Project. Aim 3: Validation of candidate susceptibility genes in a Drosopiiila model system. We will leverage the high-throughput capabilities of fly genetics, and the availability of near-saturation gain- and loss-of-function reagents for the Drosopiiila genome, to screen candidate genes identified in Aims 1 & 2 for functional interactions with Tau neurotoxicity. Aim 4: Genetic fine mapping of the most promising locus. RELEVANCE: AD is the most common neurodegenerative disease and the leading cause of dementia, with nearly 13 million individuals projected to be affected in the US by 2050. Efforts to identify risk factors and develop new therapies are therefore a priority. The discovery of genes associated with AD pathology and cognitive decline will highlight novel mechanisms of disease, identify candidate drug targets, and may facilitate early diagnosis and risk prediction.