Fine Mapping of Hypertension Genes Detected by Admixture Mapping in the FBPP

描述（由申请人提供）：尽管成功阐明了几种孟德尔疾病的病因，但定义常见复杂疾病（如心血管疾病的主要原因高血压）的遗传结构仍然是一项艰巨的挑战。我们现在有技术筛选大量的遗传变异，以查明那些潜在的特定疾病。然而，为了剖析复杂疾病的遗传基础，目前还没有建立最佳研究设计或分析策略的框架。该应用旨在开发一种研究复杂疾病的新范式，其中多阶段设计和分析方法的组合使我们能够有效地分离影响高血压风险的遗传变异。具体而言，我们建议在非裔美国人中使用祖先信息SNP标记进行混合物映射研究，然后在家庭血压计划（FBPP）招募的特征良好的队列中进行基于基因的病例对照关联研究。我们还将在不同的非洲裔美国人队列中进行进一步的复制研究，并分别估计欧洲裔美国人、墨西哥裔美国人和尼日利亚人群中已确定变异的人群特异性风险。具体目标是：1。通过混合作图法细化6号和21号染色体上现有候选区域的信息。2.在细化区域的基因中进行关联研究。3.识别基因中解释混合物作图信号的常见变异。4.表征目标3中确认的变体在其他群体样本中的影响。我们之前的研究确定了两个新的高血压候选区域（6q和21 q）（Zhu et al. 2005）。与传统的连锁研究相比，使用高信息量SNP的混合作图（Aim 1）可以实现更大的功效，并且与我们以前的混合作图分析相比，可以实现更高的分辨率，该混合作图分析使用了设计用于连锁分析的全基因组微卫星标记面板。总体而言，与单级设计相比，我们的多级设计可能实现更大的功率和更高的分辨率。

DESCRIPTION (provided by applicant): Despite the success in elucidating the etiologies of several Mendelian diseases, defining the genetic architecture of common complex diseases, such as hypertension, a major cause of cardiovascular disease, remains a daunting challenge. We now have the technology to sift through large number of genetic variants to pinpoint those underlying specific diseases. However, for dissecting the genetic basis for complex diseases, there is currently no established framework for optimal study designs or analytic strategies. This application aims to develop a novel paradigm for studying complex diseases, in which a multi-stage design and a combination of analytic methods enable us to efficiently isolate genetic variants that influencing the risk of hypertension. Specifically, we propose to perform an admixture mapping study in African Americans using ancestry-informative SNP markers, followed by gene-based case-control association studies in the well-characterized cohorts recruited by the Family Blood Pressure Program (FBPP). We will also conduct further replication studies in different African-American cohorts and estimate population specific risks for the identified variants in European-American, Mexican American and Nigerian populations, respectively. The Specific Aims are: 1. Refine information on existing candidate regions on chromosomes 6 and 21 by admixture mapping. 2. Conduct association studies in the genes in refined regions. 3. Identify common variants in genes explaining the signals in admixture mapping. 4. Characterize effects of variants confirmed in Aim 3 in other population samples. Our prior research identified two new candidate regions (6q and 21 q) for hypertension (Zhu et al. 2005). Admixture mapping using highly informative SNPs (Aim 1) may achieve a greater power compared to conventional linkage study, and achieves a higher resolution compared to our previous admixture mapping analysis, which used a genome-wide microsatellite marker panel designed for linkage analysis. Overall, our multi-stage design is likely to achieve greater power and higher resolution compared to a single-stage design.