Use of Endophenotypes in the Search for Alzheimer's Disease Risk Genes

利用内表型寻找阿尔茨海默病风险基因

基本信息

批准号：
8311728
负责人：
ALISON M GOATE
金额：
$ 56.62万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-09-01 至 2015-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8311728
关键词：
Affect Age Alzheimer&apos s Disease Alzheimer&apos s disease risk Amyloid Amyloid beta-Protein Asses Bioinformatics Biological Biological Assay Biological Markers Candidate Disease Gene Case-Control Studies Cell Culture Techniques Cerebrospinal Fluid Clinical Complex DNA Resequencing Data Data Set Defect Diabetes Mellitus Disease Disease Progression Drug Delivery Systems Funding Gene Expression Genes Genetic Genetic Crosses Genomics Goals Haplotypes Individual Information Networks Late Onset Alzheimer Disease Lead Link Malignant neoplasm of lung Messenger RNA Metabolism Methods Modeling Molecular Neurodegenerative Disorders Nicotine Dependence Pathogenesis Population Prevention Principal Investigator Process Publishing Research Resources Risk Sampling Signal Transduction Single Nucleotide Polymorphism Testing Time Trust Universities Variant base case control disease phenotype disorder prevention disorder risk endophenotype follow-up genetic risk factor genetic variant genome wide association study genome-wide human disease improved innovation member novel novel strategies programs public health relevance skills tau Proteins tau function trait

项目摘要

DESCRIPTION (provided by applicant): Several genome-wide association studies (GWAS) for late-onset Alzheimer's disease (LOAD) have now been published. While all of these studies detected the association of APOE 54 with risk for LOAD only the two largest studies, with over 10,000 cases and controls provided genome-wide significant evidence for any novel loci. To develop larger datasets we and others have formed large collaborative groups, such as the Alzheimer's Disease Genetics Consortium (ADGC). We have also developed an innovative program using cerebrospinal fluid biomarker levels as endophenotypes for our genetic studies of LOAD. Our preliminary data demonstrate the power and novelty of this approach in identifying genes that alter biomarker levels and modify LOAD risk, age at onset or rate of disease progression. This endophenotype approach also has the advantage of pin-pointing specific biological hypotheses regarding the effects of associated variants that can be tested using simple cell culture assays. The goal of this proposal is to combine and analyze existing LOAD GWAS data, then use a novel approach that incorporates quantitative intermediate traits, re-sequencing, bioinformatics, expression and functional studies to facilitate the identification and characterization of genetic variants that modulate risk for LOAD, age at onset or rate of disease progression. To accomplish this we will 1) combine and analyze LOAD GWAS data, 2) use a novel method, the Genomic Information Network, to systematically incorporate biological information to prioritize single nucleotide polymorphisms (SNPs) for follow-up, 3) examine top SNPs from the LOAD GWAS for association with cerebrospinal fluid amyloid-beta and tau levels to establish specific hypotheses of mechanism, 4) use novel genetic and bioinformatic methods to identify putative causal variants from the replicated SNPs, 5) use re-sequencing to identify novel variants in the regions surrounding replicated SNPs, 6) examine the top hits for effects on gene expression. Finally, we will use information from these efforts to test specific amyloid-beta or tau related hypotheses for replicated SNPs in cell culture models. This proposal combines the unique resources and skills of our research team with the vast wealth of publicly available resources into a novel approach to the identification and characterization of genetic risk factors for LOAD. PUBLIC HEALTH RELEVANCE: Alzheimer's disease is a very common neurodegenerative disease with no effective means of prevention or treatment. The goal of the present study is to identify genetic risk factors for Alzheimer's disease, which in the longer term may lead to novel drug targets and improved treatment/prevention of the disease.

描述（由申请人提供）：现已发表了几项针对晚期阿尔茨海默氏病（负载）的全基因组关联研究（GWAS）。尽管所有这些研究都检测到APOE 54与载荷的风险仅相关的两项最大研究的风险，而超过10,000例病例和对照为所有新型基因座提供了全基因组的重要证据。为了开发较大的数据集，我们和其他人组成了大型协作群体，例如阿尔茨海默氏病遗传学联盟（ADGC）。我们还使用脑脊液生物标志物水平作为我们的负载遗传研究的内型型开发了一个创新的程序。我们的初步数据证明了这种方法在识别改变生物标志物水平并改变载荷风险，发作时年龄或疾病进展速率的基因的能力和新颖性。这种内表型方法还具有针对可以使用简单的细胞培养分析测试的相关变体的影响的针对特定的生物学假设的优点。该提案的目的是结合和分析现有的负载GWAS数据，然后使用一种新型方法，该方法结合了定量性中间性状，重新序列，生物信息学，表达和功能研究来促进遗传变异的识别和表征，从而调节疾病的疾病的风险，年龄或疾病进展。为此，我们将1）结合和分析负载GWAS数据，2）使用一种新方法，基因组信息网络，系统地结合生物学信息，以优先考虑单个核苷酸多态性（SNP），以进行随访，以进行后续研究，3）检查与脑脊髓液体级别相关的载荷量的高负gaus and taue and taue级别，以建立特定的beta和taue级别，以建立特定的bete级tau级和taue级的含量。生物信息学方法可以从复制的SNP中识别推定的因果变体，5）使用重新测序来识别复制的SNP周围地区的新型变体，6）检查最高命中是否对基因表达的影响。最后，我们将使用这些努力中的信息来测试细胞培养模型中复制SNP的特定淀粉样蛋白β或与TAU相关的假设。该建议将我们研究团队的独特资源和技能与大量公开资源结合在一起，成为一种新颖的方法，以识别和表征负载遗传风险因素。公共卫生相关性：阿尔茨海默氏病是一种非常普遍的神经退行性疾病，没有有效的预防手段或治疗手段。本研究的目的是确定阿尔茨海默氏病的遗传危险因素，从长远来看，这可能导致新颖的药物靶标并改善治疗/预防疾病。