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）：与年龄相关的黄斑变性（AMD）是西方国家老年人口失明的主要原因。在过去的几年中，通过个人研究或通过国家眼睛研究所（NEI）支持AMD基因联盟的多项研究的荟萃分析，通过全基因组关联研究（GWAS）确定了超过十二个AMD风险基因座。在38,000 AMD/控制对象上进行的外显子芯片实验将通过发现其他稀有变体进一步扩大列表。但是，分析和统计方法仍落后于数据生成的速度。来自我们的合作者，AMD Exome CHIP联盟以及公共数据库（例如DBGAP）的新兴遗传和表型数据将使我们能够检验新的假设，开发和校准统计方法，以促进我们参与其中参与其中的正在进行的联盟研究。特别是，我们有兴趣系统地研究AMD进展的遗传原因和预测，在非裔美国人队列中识别疾病敏感性基因座，以及开发具有二进制特征的基于家庭研究的关联方法。为了实现这些目标，我们提出了以下特定目的：1）开发双变量生存框架，以共同对眼睛的AMD进展进行建模，并使用AREDS（年龄相关的眼科研究）的4,000多个合格样本对AMD进展进行全基因组进展研究，AREDS2，AMD研究，以及在密歇根州大学的University of Michigan of Michigan of Michigans of Michigan of Michigans of Michigans; 2）从AIM 1的结果中，基于人口统计，临床和遗传信息来开发和验证严格的统计模型，以预测AMD的发生和进展，并获得有关不同研究设计的预测概率以及两只眼睛之间的相关性； 3）开发和应用新颖的方法来识别725名无关的非裔美国人中与AMD风险相关的基因座，结合了关联和混合映射的信号； 4）使用功能建模方法在广义线性混合模型框架下开发一种稀有变体关联测试的二进制特征测试，并将方法应用于我们的UCLA-匹兹堡家庭基于2,188个样本的研究。我们的结果将提高我们对发病机理和预防AMD发生及其进展的理解。我们开发和应用的方法将用于其他研究组，并将有益于正在进行的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。我们的研究团队的独特优势包括：在AMD数据集的应用分析，出色的统计遗传学专业知识和临床顾问的应用分析中，具有丰富的先前经验，并深入了解了他们收集的AMD数据集。成功完成我们的目标，我们将开发和应用最先进的统计方法，将丰富我们对AMD发病机理的理解并改善个人风险预测，因此将有助于增强临床实践。