GWAS FOR CARDIOVASCULAR HEALTH IN ELDERLY PUERTO RICANS

基因分析的迅速发展为人口健康揭开了令人兴奋的一章。一直 在报告基因和pol 5 tnorphisms可能影响健康的结果是一个巨大的上升。 特别是，全基因组扫描技术和生物信息学提供了令人兴奋的信息， 疾病风险。然而，大多数可用的数据，特别是全基因组关联（GWAS）研究， 基于非西班牙裔白色人群。随着美国西班牙裔人口的预计增长， 随着这一人群健康差异的增加，将其纳入遗传学研究势在必行。我们提供了一个 独特的资源，因为我们有一群拥有DNA的波多黎各成年人，而且范围广泛， 详细的表型数据。据我们所知，这是对这类波多黎各人进行的最大规模的队列研究。的 这个群体的遗传学以前没有被研究到这种程度和强度，因此， 补充GWAS联盟的目标。我们vAW集中在两个普遍的情况下看到，在过度 该人群：高血压和2型糖尿病，因为它与心血管疾病（CVD）有关。在我们 NIH资助的人口健康和健康差异中心（CPHHD，5 P01-AG 023394），我们有一个 纵向研究1450波多黎各成年人，年龄45-75岁。这项研究包括人口统计数据， 社会经济学、饮食摄入量和健康行为、人体测量、生物化学和 基因5 q）的150多个遗传变异。此外，我们已经完成了两年多的采访， 900例受试者正在接受随访。GWAS将提供一种有效的方法来促进我们对 健康差异，并作为风险过高的人群，找出导致这些差异的新遗传因素 条件使用GWAS结合深入的生物信息学分析，我们将进一步优先考虑450 与CVD和风险相关的SNP。选择的SNP将在其他两个群体中复制： 降脂药物和饮食网络（GOLDN）的遗传学，我们正在进行GWAS。 老年人营养、衰老和记忆研究（NAME）是一项老年队列研究， 血管健康和h3 T1高血压和糖尿病的高患病率的富集表型。基础上 从其他四个项目的结果，我们将探讨基因型与环境变量的相互作用， 包括饮食、体育活动、文化适应和压力测量，以增加对 CVD。虽然人口规模可能看起来很小，但慢性病的高流行率，如 高血压和糖尿病，以及我们在检测心血管疾病遗传相关性方面的成功， 风险证明该人群对GWAS具有足够的把握度。这项研究的结果结合了 与其他四个项目相比，vnll使我们能够（1）提供一个完整的遗传特征谱， 心血管疾病的这一人口;（2）创造一个新的理解的健康差距方面的基础， 遗传学和环境（饮食和生活方式）;（3）在另外两个方面确认潜在的遗传关系 人口。

The rapid developments in genetic analyses have opened an exciting chapter in population health. There has been a tremendous rise in the reporting of genes and pol5Tnorphisms potentially impacting health outcomes. In particular, genome wide scanning technology and bioinformatics are providing exciting information on disease risk. However, most available data, and particularly genome-wide association (GWAS) studies, are based on non-Hispanic white populations. With the projected increase ofthe US Hispanic population and the rise of health disparities in this population, their inclusipn in genetic studies is imperative. We provide a unique resource, in that we have a cohort of Puerto Rican adults with DNA available, and extensive and detailed phenotypic data. To our knowledge, this is the largest cohort study of Puerto Ricans of this type. The genetics of this population has not been studied before to this extent and intensity, and this will, therefore, complement the goals ofthe GWAS consortium. We vAW focus on two prevalent conditions seen in excess in this population: hypertension and type 2 diabetes as it relates to cardiovascular disease (CVD). Within our NIH funded Center on Population Health and Health Disparities (CPHHD, 5P01-AG023394), we have a longitudinal study of 1450 Puerto Rican adults, aged 45-75 y. The study includes data on demographics, socio-economics, dietary intake and health behaviors, anthropometric measures, biochemistries and genot5q)es of over 150 genetic variants. Further, we have already completed 2-year-interviews of more than 900 subjects in our ongoing follow-up. GWAS will provide an efficient way to advance our understanding of health disparities and, as a population with excess risk, to identify novel genetic contributors to these conditions. Using GWAS in conjunction with in-depth bioinformatic analyses, we will further prioritize 450 SNPs that are associated with CVD and risk. Selected SNPs will be replicated in other two populations: the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), for which a GWAS is being conducted in our laboratotory, and the Nutrition, Aging, and Memory in Elders Study (NAME), an elderly cohort which has enriched phenotypes for vascular health and high prevalance of h3T)ertension and diabetes. Building on findings from the four other projects, we will explore genotype interaction with environmental variables, including diet, physical activity, acculturation and measures of stress to increase understanding ofthe risk of CVD. While the population size may appear small, the high prevalence of chronic diseases, such as hypertension and diabetes in this population and our success in detecting genetic associations for CVD and risk demonstrate the sufficient power of this population for GWAS. The findings from this study combined with those ofthe four other projects vnll allow us to (1) provide a fiill spectrum of genetic characteristics of CVD of this population; (2) create the foundation for a new understanding of health disparities in terms of genetics and environment (diets and lifestyle); (3) confirm potential genetic relationships in two additional populations.