Genome-Wide Association Analysis of Bladder Cancer

膀胱癌的全基因组关联分析

• 批准号: 7591153
• 负责人: Xifeng Wu
• 金额: $ 109.06万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7591153
• 关键词: Adopted; Age; Algorithms; Architecture; Arts; Biological; Biological Assay; Bladder; Cancer Center; Cancer Etiology; Case Series; Case-Control Studies; Cell Cycle Regulation; Chemoprevention; Chemopreventive Agent; Clinic; Clinical; Complex; Computational algorithm; Custom; Cytogenetics; DNA; DNA Repair; Data; Databases; Dietary Practices; Disease; Doctor of Medicine; Environment; Environmental Exposure; Environmental Risk Factor; Epidemiology; Ethnic Origin; Frequencies; Funding; Future; Gender; Genes; Genetic; Genetic Polymorphism; Genetic Risk; Genetic Variation; Genomics; Genotype; Goals; Haplotypes; Health Benefit; Human Genome; Individual; Individual Differences; Inherited; International; Intervention; Joints; Length; Light; Location; Lymphocyte; Machine Learning; Malignant neoplasm of urinary bladder; Maps; Medicine; Modeling; Molecular; Mutagens; New England; New Hampshire; Newly Diagnosed; Occupational Exposure; One-Step dentin bonding system; Outcome; Pattern; Penetrance; Phenotype; Physicians; Plasma Cells; Play; Polymorphism Analysis; Population; Predisposition; Public Health; Recruitment Activity; Reproduction spores; Resources; Review Literature; Risk; Role; Sampling; Screening procedure; Serum; Single Nucleotide Polymorphism; Smoking; Specimen; Staging; Statistical Methods; Subgroup; Suspension substance; Suspensions; TNFRSF5 gene; Technology; University of Texas M D Anderson Cancer Center; Validation; Variant; aggregation pathway; base; cancer risk; carcinogenesis; case control; college; computer based statistical methods; cost; density; design; epidemiologic data; follow-up; gene interaction; genome wide association study; genome-wide; high risk; medical specialties; novel; parent grant; public health relevance; repository; telomere; tool

DESCRIPTION (provided by applicant): This proposal builds on a rich resource of bladder cancer (BC) cases and controls derived from two ongoing BC studies at the University of Texas M.D. Anderson Cancer Center, and from two large independent U.S. BC studies - the New England BC Study and the New Hampshire BC Study. The goal is to identify genetic loci that predispose individuals to BC through a genome-wide scanning approach. There are five specific aims. Aim 1 is to first perform genome-wide, high-density SNP genotyping using the Illumina HumanHap550 SNP platform on 800 cases and 800 controls from M.D. Anderson, with a target of candidate SNPs of about 28,000; followed by an internal validation to narrow down candidate SNPs to about 1,536 using additional 800 pairs of cases and controls. Illumina's Custom Infinium array will be the genotyping format. In this aim, in addition to individual SNP analysis, we will also implement haplotype-based analyses and pathway aggregation analysis to identify additional genetic loci that might have been overlooked using individual SNP analysis. Aim 2 is the first external validation of the 1,536 SNPs from Aim 1 using 1,000 pairs of cases and controls from the New England BC Study. Illumina's GoldenGate assay will be the genotyping format. After this stage, the candidate SNPs will be narrowed down to about 100. Aim 3 is the second independent external validation using 750 pairs of cases and controls form the New Hampshire BC Study. In this aim, the 100 top candidate SNPs passed from Aims 1 and 2 plus additional functional SNPs in genes containing these SNPs will be genotyped. GoldenGate assay will be used for this aim. Aim 4 is to perform fine mapping studies in the flanking regions of each of the top 25 SNP loci confirmed in Aim 3 to identify causative loci. This will utilize all 6,700 cases and controls. An average of 15 additional SNPs (tagging SNPs and functional SNPs) per gene is expected. Aim 5 is to apply novel machine-learning tools to identify any gene-environment and gene-gene interactions greatly influencing risk for BC in all the 6700 subjects. These analyses will be utilized to examine SNP main effect and develop and validate algorithms that will identify individuals at highest risk for BC, given their personal exposure patterns and their genetic risk profiles. This proposal applies state of art technology to perform a multistage, genome-wide SNP analysis in three largest, well-characterized U.S. population of BC cases and controls, and incorporates complete epidemiologic data and rich and unique functional data. In addition, results from this study will be provided to the International Consortium of BC Case Control Studies for future validation. The ability to identify genetically susceptible, high-risk subgroups that would benefit from intensive screening and/or chemopreventive interventions is of immense clinical and public health benefit. PUBLIC HEALTH RELEVANCE Bladder cancer (BC) is a disease mainly caused by smoking and occupational exposure. However, only a small percentage of exposed individuals develop BC. Inherited host genetic factors may play an important role in determining an individual's susceptibility to BC. This proposal builds on three largest well-characterized U.S. populations of BC cases and controls - the M. D. Anderson BC study, the New England BC Study and the New Hampshire BC Study. A total of 6700 cases and controls will be used. The goal is to identify genetic loci that predispose individuals to BC through a non-biased, discovery- driven, genome-wide scanning approach and to incorporate complete epidemiologic data and rich and unique functional data. About 550,000 genetic variations of human genome will be initially screened in an M.D. Anderson population consisting of an equal number of BC cases and normal controls. About 28,000 top candidate variations that are potentially associated with increased BC risk will be first narrowed down and internally replicated in a second M.D. Anderson population, and then be validated in the other two independent U.S. BC populations. Finally, the causative genetic loci that predispose individuals to BC will be mapped. This study is significant because by identifying BC susceptibility loci, it will shed light into the biological mechanisms of BC etiology. Furthermore, it may facilitate identifying high-risk subgroups of individuals for BC, given their genetic makeup and environmental exposures. The ability to identify high-risk subgroups of individuals for BC will provide immense public health benefit for those high- risk people who may be subjected to close surveillance and chemoprevention.

描述(由申请人提供)： 这项建议建立在丰富的膀胱癌病例和对照资源的基础上，这些病例和对照来自德克萨斯大学安德森癌症中心正在进行的两项膀胱癌研究，以及两项大型的独立美国膀胱癌研究--新英格兰膀胱癌研究和新汉普郡膀胱癌研究。其目标是通过全基因组扫描的方法确定使个体易患BC的遗传位点。有五个具体目标。目标1是首先使用Illumina Human Hap550 SNP平台对800例M.D.Anderson的病例和800名对照进行全基因组高密度SNP基因分型，目标是大约28,000个候选SNP；然后使用另外800对病例和对照进行内部验证，将候选SNP缩小到约1,536个。Illumina的定制Infinium阵列将是基因分型格式。为此，除了个体SNP分析外，我们还将实施基于单倍型的分析和路径聚合分析，以确定可能被个体SNP分析忽略的其他遗传位点。AIM 2是首次对来自AIM 1的1,536个SNP进行外部验证，使用了来自新英格兰不列颠哥伦比亚省研究的1,000对病例和对照。Illumina的金门试验将是基因分型的形式。在这一阶段之后，候选SNPs的范围将缩小到大约100个。AIM 3是第二个独立的外部验证，使用了来自新汉普郡BC研究的750对病例和对照。在这个目标中，将对从AIMS 1和AIMS 2传递的100个顶级候选SNPs以及包含这些SNPs的基因中的额外功能SNPs进行基因分型。为此，将使用金门试验。目标4是对目标3中确认的前25个SNP基因座的侧翼区域进行精细定位研究，以确定致病基因座。这将利用所有6700个病例和对照。预计每个基因平均增加15个SNPs(标记SNPs和功能性SNPs)。目标5是应用新的机器学习工具来识别所有6700名受试者中任何对BC风险有重大影响的基因-环境和基因-基因交互作用。这些分析将被用来检查SNP的主要影响，并开发和验证算法，根据他们的个人暴露模式和他们的遗传风险概况，识别BC风险最高的个人。这项建议应用最先进的技术对三个最大的、特征良好的美国BC病例和对照人群进行了多阶段的全基因组SNP分析，并结合了完整的流行病学数据和丰富而独特的功能数据。此外，这项研究的结果将提供给不列颠哥伦比亚省病例控制研究国际联合会，以供将来验证。能够确定将从密集筛查和/或化学预防干预中受益的遗传易感、高危亚群的能力具有巨大的临床和公共卫生益处。与公共卫生相关的膀胱癌(BC)是一种主要由吸烟和职业暴露引起的疾病。然而，只有一小部分暴露于此的人会患上BC。遗传宿主遗传因素可能在决定个体对BC的易感性方面发挥重要作用。这项建议建立在美国三个最大的BC病例和对照人群的基础上--M.D.安德森BC研究、新英格兰BC研究和新汉普郡BC研究。总共将使用6700个病例和对照。其目标是通过一种无偏见的、发现驱动的全基因组扫描方法识别易患BC的遗传基因座，并结合完整的流行病学数据和丰富而独特的功能数据。大约550,000个人类基因组的遗传变异将在M.D.Anderson人群中进行初步筛选，该人群由数量相等的BC病例和正常对照组成。大约28,000个可能与BC风险增加相关的顶级候选变异将首先缩小范围，并在第二个M.D.Anderson群体中进行内部复制，然后在另外两个独立的美国BC群体中进行验证。最后，将绘制易患BC的致病遗传基因座的图谱。这项研究具有重要意义，因为通过确定BC易感基因座，将有助于揭示BC病原学的生物学机制。此外，考虑到他们的基因构成和环境暴露，这可能有助于确定BC的高危个体亚群。识别BC高危人群的能力将为那些可能受到密切监测和化学预防的高危人群提供巨大的公共卫生益处。