AMD genetics: methods and analysis for progression, prediction, and association

AMD 遗传学：进展、预测和关联的方法和分析

• 批准号: 8662338
• 负责人: Wei Chen
• 金额: $ 30.11万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8662338
• 关键词: Accounting; Address; Admixture; African American; Age related macular degeneration; Blindness; Case-Control Studies; Caucasians; Caucasoid Race; Clinical; Communities; Computer software; Country; Data; Data Analyses; Data Set; Databases; Deposition; Development; Disease; Disease susceptibility; Elderly; Ensure; Eye; Eye diseases; Family; Future; Generations; Genes; Genetic; Genetic Research; Genome; Genomics; Glaucoma; Goals; Individual; Maps; Meta-Analysis; Methods; Michigan; Modeling; National Eye Institute; Paper; Pathogenesis; Performance; Phase; Phenotype; Population; Predisposition; Prevalence; Prevention; Preventive Intervention; Probability; Research; Research Design; Research Project Grants; Resources; Risk; Sampling; Signal Transduction; Statistical Methods; Statistical Models; Survival Analysis; Testing; Time; United States National Institutes of Health; Universities; Variant; Vision; Vision research; age related; base; clinical practice; cohort; database of Genotypes and Phenotypes; exome; experience; genetic epidemiology; genetic variant; genome wide association study; improved; insight; interest; markov model; multidisciplinary; novel; predictive modeling; programs; public health relevance; rare variant; research study; response; risk variant; success; tool; trait; user-friendly

DESCRIPTION (provided by applicant): Age-related macular degeneration (AMD) is a leading cause of blindness in the elderly population of Western countries. In the past few years, over one dozen AMD risk loci have been identified through genome-wide association studies (GWAS), either by individual studies or through meta-analyses of multiple studies from the National Eye Institute (NEI) supported AMD Gene Consortium. An ongoing exome chip experiment on 38,000 AMD/Control subjects will further expand the list by discovering additional rare variants. However, the analyses and statistical methods are still lagging behind the pace of data generation. Emerging genetic and phenotypic data from our collaborators, the AMD Exome Chip Consortium, and public databases (e.g. the dbGaP) will allow us to test new hypotheses, develop and calibrate statistical methods to facilitate ongoing consortium studies in which we are involved. In particular, we are interested in systematically studying the genetic causes and prediction of AMD progression, identifying disease-susceptibility loci in a cohort of African Americans, and developing association methods for family-based studies with binary traits. To achieve these goals, we propose specific aims as follows: 1) To develop a bivariate survival framework to jointly model AMD progression in both eyes and to perform a genome-wide association study of AMD progression using over 4,000 eligible samples from AREDS (Age-Related Eye Disease Study), AREDS2, and the AMD study conducted at the University of Michigan; 2) To develop and validate rigorous statistical models for prediction of AMD occurrence and progression based on demographic, clinical, and genetic information from the results of Aim 1 and to obtain predictive probabilities accounting for different study designs and the correlation between two eyes; 3) To develop and apply novel methods to identify loci associated with AMD risk in 725 unrelated African Americans, combining signals from both association and admixture mapping; and 4) To develop a statistical method for rare variant association tests of binary traits in families under the framework of generalized linear mixed model using a functional modeling approach and to apply the method to our UCLA- Pittsburgh family-based study of 2,188 samples. Our results will advance our understanding of pathogenesis and prevention of AMD occurrence and its progression. The methods we developed and applied will be available to other study groups and will benefit the analysis of ongoing AMD consortium data. In addition, our methods can be applied to other vision research as well. Unique strengths of our research team include: extensive prior experience in the applied analyses of AMD data sets, outstanding statistical genetics expertise, and clinical consultants with deep insight into the AMD data sets they collected. Successful completion of our Aims, where we will develop and apply state-of-the-art statistical methods, will enrich our understanding of AMD pathogenesis and improve individual risk prediction, and therefore will help enhance clinical practice.

描述（由申请人提供）：年龄相关性黄斑变性（AMD）是西方国家老年人口失明的主要原因。在过去的几年中，通过全基因组关联研究 (GWAS)，无论是通过单独的研究，还是通过国家眼科研究所 (NEI) 支持的 AMD 基因联盟的多项研究的荟萃分析，已经确定了十多个 AMD 风险位点。一项正在进行的针对 38,000 名 AMD/对照受试者的外显子组芯片实验将通过发现其他罕见变异来进一步扩大列表。然而，分析和统计方法仍然落后于数据产生的步伐。来自我们的合作者、AMD 外显子组芯片联盟和公共数据库（例如 dbGaP）的新出现的遗传和表型数据将使我们能够测试新的假设，开发和校准统计方法，以促进我们参与的正在进行的联盟研究。我们特别感兴趣的是系统地研究 AMD 进展的遗传原因和预测，识别非裔美国人群体中的疾病易感位点，并开发基于家庭的二元性状研究的关联方法。为了实现这些目标，我们提出了如下具体目标：1）开发一个双变量生存框架来联合模拟双眼的 AMD 进展，并使用来自 AREDS（年龄-年龄）的 4,000 多个合格样本进行 AMD 进展的全基因组关联研究。相关眼病研究）、AREDS2 和密歇根大学进行的 AMD 研究； 2) 根据目标 1 结果中的人口统计、临床和遗传信息，开发和验证严格的统计模型，用于预测 AMD 的发生和进展，并获得考虑不同研究设计和两只眼睛之间相关性的预测概率； 3) 开发并应用新方法来识别 725 名无关非裔美国人中与 AMD 风险相关的基因座，结合来自关联和混合图谱的信号； 4) 使用函数建模方法，在广义线性混合模型框架下开发一种用于家庭二元性状罕见变异关联测试的统计方法，并将该方法应用于我们基于加州大学洛杉矶分校-匹兹堡分校的 2,188 个样本的家庭研究。我们的结果将增进我们对 AMD 发生及其进展的发病机制和预防的理解。我们开发和应用的方法将可供其他研究小组使用，并将有利于对正在进行的 AMD 联盟数据的分析。此外，我们的方法也可以应用于其他视觉研究。我们研究团队的独特优势包括：在 AMD 数据集应用分析方面的丰富经验、出色的统计遗传学专业知识以及对他们收集的 AMD 数据集有深入了解的临床顾问。我们将开发和应用最先进的统计方法，成功完成我们的目标，将丰富我们对 AMD 发病机制的理解并改善个体风险预测，因此将有助于加强临床实践。