Analysis of Genome-Wide Data in the Health and Retirement Study

 描述(由申请人提供)：健康与退休研究(HRS)有潜力成为一般社会科学遗传学的关键资源，特别是衰老的行为基因组学，因为它的样本量相对较大，其丰富的纵向行为测量，以及大约13,000名美国老年人的密集基因组数据的可用性，还有7,000多人的数据正在准备中。这项拟议的研究将使用HRS丰富的表型、遗传和环境数据来寻求两种互补的策略。一是将HRS数据纳入由申请者组织的社会科学遗传协会联合会(SSGAC)主持下进行的行为表型大型联合会元分析中。第二种策略是使用HRS数据来测试从该联盟的发现中产生的特定假设，并阐明HRS中测量的丰富的行为表型集的遗传结构-即遗传效应大小和等位基因频率的联合分布。我们的总体目标是使用HRS的表型、遗传和环境数据来显著促进对行为基因组学的总体理解，特别是对美国老年人的经济行为、健康和福祉的理解。我们建议的目标包括：(A)发现与重要的行为结果、心理特征和经济偏好相关的特定遗传多态；(B)分析这些关联背后的生物学途径；(C)开发多基因评分(许多多态的指数)，当用大样本估计的权重构建时，将对行为表型具有实质性的预测能力；(D)识别与特定多态和多基因评分之间的联系的行为机制(即内表型)；(E)分析在HRS中测量的一系列表型的遗传结构；以及(F)基因-环境相互作用的检查。

 DESCRIPTION (provided by applicant): The Health and Retirement Study (HRS) has the potential to become a critical resource in social-science genetics in general, and the behavioral genomics of aging in particular, due to its relatively large sample size, its rich longitudinal behavioral measures, and the availability of dense genomic data for approximately 13,000 older Americans, with data on 7,000 more on the way. The proposed research will use the HRS's rich phenotypic, genetic, and environmental data to pursue two complementary strategies. One is to incorporate HRS data into large consortium meta-analyses of behavioral phenotypes conducted under the auspices of the Social Science Genetic Association Consortium (SSGAC), which the applicants organize. The second strategy is to use the HRS data to test specific hypotheses arising from the consortium's findings and to shed light on the genetic architecture-i.e., the joint distribution of genetic effect sizes and allele frequencies-of the rich set of behavioral phenotypes measured in the HRS. Our general aim is to use the phenotypic, genetic, and environmental data from the HRS to significantly advance understanding of behavioral genomics in general, and of the economic behavior, health, and well- being of older Americans in particular. Among the goals of our proposal are: (a) discoveries of specific genetic polymorphisms that are associated with important behavioral outcomes, psychological characteristics, and economic preferences; (b) analysis of biological pathways that underlie these associations; (c) development of polygenic scores (indexes of many polymorphisms) that, when constructed with weights estimated in large samples, will have substantial predictive power for behavioral phenotypes; (d) identification of behavioral mechanisms (i.e., endophenotypes) that mediate associations with specific polymorphisms and polygenic scores; (e) analysis of the genetic architecture of a range of phenotypes measured in the HRS; and (f) examination of gene-environment interactions.