Allele-specific Mapping in Alzheimer's Disease

描述（由申请人提供）：在阿尔茨海默病（AD）的研究中，许多先前的重点是遗传研究，这些研究已经揭示了APP，APOE和PS1基因的基本参与。但除了APOE的多态性外，这些基因中已知的编码变异非常罕见，现有的数据不能完全解释一般人群中迟发性AD（LOAD）的遗传性。全基因组关联研究（GWAS）和相关的高通量基因组扫描已经发现了影响AD易感性的其他染色体位点，但复制不均匀，致病或易感基因尚未明确定位。此外，还不可能测量这些扫描中的许多亚阈值统计峰值的重要性。需要新的方法来克服这些障碍，我们相信，首先获得人类大脑皮层中具有序列依赖性等位基因特异性甲基化（ASM）和/或等位基因特异性mRNA表达（ASE）的位点列表，然后将这些信息与GWAS的统计峰值重叠的组合策略将有助于解决这个问题。我们将使用基于微阵列和基于测序的方法在人类大脑皮层中筛选ASM/ASE。我们将使用独立的检测方法验证ASM/ASE的最强候选基因座，并将这些基因座的列表与LOAD中现有和正在进行的GWAS的数据重叠。来自这2个数据集的交叉点的基因座将在LOAD病例和对照的3个独立的充分表征的群组中进行高度集中的且因此具有成本效益的遗传精细作图。我们的推理是，序列依赖性ASM/ASE在或附近的特定基因在大脑皮层中将是一个强大的指标，真正的顺式作用的调节多态性（rSNPs，rCNPs）的存在，赋予个体间的差异，在人类大脑皮层中的特定基因的表达，并在这组基因将是一些导致个体间差异的LOAD易感性。来自GWAS和LOAD的相关基因组扫描的可再现信号与显示ASM和/或ASE的基因座重叠，因此将具有强大的功能基础，并保证进一步深入研究作为LOAD的生物学贡献者和潜在治疗靶点。 公共卫生相关性：我们的项目是一个结合遗传和表观遗传的方法来了解阿尔茨海默病（AD）的发病机制，阿尔茨海默病是一种神经元退行性疾病，是年龄相关性痴呆的最常见原因。我们将使用基于微阵列和基于测序的方法来鉴定具有遗传决定的人类大脑中DNA甲基化和RNA表达个体间差异的基因组。我们将把这个基因列表与现在从全基因组关联研究（GWAS）中出现的AD易感性候选基因列表重叠，我们将对在两种类型的数据中得分为阳性的基因和染色体区域进行精细定位。通过这种策略，我们希望能够更有信心地确定影响AD易感性的基因。

DESCRIPTION (provided by applicant): Much prior emphasis in research on Alzheimer's disease (AD) has been on genetic studies, which have uncovered the fundamental involvement of the APP, APOE and PS1 genes. But with the exception of polymorphisms in APOE, known coding variants in these genes are quite rare, and the existing data do not fully account for the heritability of late-onset AD (LOAD) in the general population. Additional chromosomal loci putatively influencing AD susceptibility have been uncovered by genome-wide association studies (GWAS) and related high-throughput genomic scans, but replication has been uneven and the causative or predisposing genes have not been clearly pinpointed. Further it has not been possible to gauge the importance of numerous sub-threshold statistical peaks in these scans. New approaches are needed to get through these roadblocks, and we believe that a combined strategy to first obtain lists of loci with sequence-dependent allele-specific methylation (ASM) and/or allele-specific mRNA expression (ASE) in human cerebral cortex, and then overlap this information with statistical peaks from GWAS, will help to solve this problem. We will screen for ASM/ASE in human cerebral cortex using microarray-based and sequencing-based methods. We will validate the strongest candidate loci for ASM/ASE using independent assays, and overlap the list of such loci with data from existing and ongoing GWAS in LOAD. Loci from the intersection of these 2 datasets will be subjected to highly focused and thus cost efficient genetic fine mapping in 3 independent well characterized cohorts of LOAD case and controls. Our reasoning is that sequence-dependent ASM/ASE in or near specific genes in the cerebral cortex will be a robust indicator for the presence of bona fide cis-acting regulatory polymorphisms (rSNPs, rCNPs) that confer inter-individual differences in the expression of specific genes in the human cerebral cortex, and that within this set of genes will be some that cause inter-individual differences in LOAD susceptibility. Reproducible signals from GWAS and related genome scans for LOAD that overlap with loci that show ASM and/or ASE will thus have a strong functional underpinning and warrant further intensive study as biological contributors and potential therapeutic targets in LOAD. PUBLIC HEALTH RELEVANCE: Our project is a combined genetic and epigenetic approach to understand the pathogenesis of Alzheimer's disease (AD), a degenerative disorder of neurons that is the most common cause of age-related dementia. We will use microarray-based and sequencing-based methods to identify the set of genes with genetically determined inter-individual differences in DNA methylation and RNA expression in the human brain. We will overlay this list of genes with lists of AD susceptibility candidate genes that are now emerging from genome- wide association studies (GWAS), and we will carry out fine mapping of the genes and chromosomal regions that score positively in both types of data. By this strategy we expect to be able to more confidently identify genes that affect susceptibility to AD.