Alzheimer's Disease Genetics Consortium

描述（由申请人提供）：GWA方法现在已经成功地用于检测越来越多的遗传复杂疾病的疾病相关易感基因。在这些研究中，成功的一个关键因素是样本量足够大，以便有足够的能力来检测在全基因组意义上具有适度效应大小的基因。检测给定效应大小所需的样本取决于遗传异质性，这对于阿尔茨海默病是难以预测的。然而，对于其他疾病，如2型糖尿病，易感基因的比值比约为1.3，初始发现队列为4,549例病例和5,579例对照（合并1,3期研究），随后的复制数据集为10,053例病例和12,289例对照（2期）。目前的基因分型平台允许使用约55万个SNP覆盖约92%的人类基因组连锁不平衡景观。通常，在发现阶段名义上检测到的顶级SNP的约1%随后在复制数据集中进行测试。在最初的发现实验中，验证的位点不在SNP的顶层，这并不罕见。因此，大量的复制样本对这些研究的成功至关重要。就准确诊断而言，复制样本的质量对GWA研究的成功至关重要，因为不正确的诊断可能导致确认真实基因座的能力降低。ADGC的成立是为了协同利用阿尔茨海默病研究界的集体资源来鉴定阿尔茨海默病基因。临床，神经病理学，分子和统计专家存在于阿尔茨海默病研究界。此外，许多所需的表型数据和DNA样本也存在，由adc收集。ADGC的主要目标是确定影响AD易感性的基因变异。易感基因可能影响疾病的发病年龄、前驱和轻度认知障碍（MCI）阶段的进展速度。次要目标是确定影响特定AD相关内表型的基因，如神经病理学特征（如淀粉样蛋白负荷，缠结负荷等），生物标志物测量(如脑脊液（CSF） A？和tau水平，MRI测量]，疾病进展率，对环境因素（如药物，非药物环境因素）的反应。

DESCRIPTION (provided by applicant): GWA methods have now been successfully used to detect disease-related susceptibility genes for a growing 1st of genetically complex disorders. In these studies, a critical element for success is that the sample size be large enough so that there is adequately power to detect genes with modest effect sizes at genome-wide significance. The sample needed to detect a given effect size depends on genetic heterogeneity, which is difficult to predict for AD. However, for other diseases such as type 2 diabetes, susceptibility genes with odds ratios of ~1.3 have been detected with initial discovery cohorts of 4,549 cases and 5,579 controls (phase 1, 3 studies combined) followed by a replication dataset of 10,053 cases and 12,289 controls (phase 2). Current genotyping platforms permit coverage of ~92% of the linkage disequilibrium landscape of the human genome using ~550,000 SNP's. Typically, ~1% of the top SNP's nominally detected in the discovery phase are then tested in the replication dataset. It is not unusual that validated loci not in the top tier of SNP's from the initial discovery experiment. Thus a large replication samples is critical to the success of these studies. The quality of the replication samples in terms of accurate diagnosis is critical to the success of GWA studies because incorrect diagnoses can result in reduced power to confirm true loci. The ADGC is being formed to collaboratively use the collective resources of AD research community to identify AD genes. The clinical, neuropathologic, molecular and statistical expertise exists within the AD research community. Also, much of the needed phenotype data and DNA samples also exist, gathered by the ADCs. The primary goal of the ADGC will be to identify variability in genes that influences susceptibility to AD. Susceptibility genes potentially influence onset-age, rate of progression through the prodromal and mild cognitive impairment (MCI) phase of the disease. Secondary goals are to identify genes that influence specific AD- related endophenotypes such as neuropathology features (e.g. amyloid load, tangle load, etc), biomarker measures [e.g. cerebral spinal fluid (CSF) A? and tau levels, MRI measures], rate-of-disease progression, responses to environmental factors (e.g. drugs, non-pharmaceutical environmental factors).