Exonic variants and their relation to complex traits in minorities of the WHI

描述（由申请人提供）：在当前的PAGE研究（PAGE 1）中，我们研究了通过全基因组关联研究（GWAS）在祖先多样的人群中鉴定的许多遗传基因座，并成功地从欧洲血统人群的研究中概括和精细定位了许多GWAS基因座。这些成功支持将基因组搜索扩展到不太常见和罕见的变异，这些变异在GWAS中尚未捕获，但代表了基因组中遗传变异的最大部分，并有助于许多复杂性状的遗传性。大多数GWAS都是在欧洲人中进行的;然而，需要研究遗传风险因素（包括低频变异）对不同人群中常见复杂性状的影响，包括研究不足的美国少数民族，这些少数民族有很高的疾病负担。该项目的目标是全面调查基因组蛋白质编码区（即“外显子组”）中频率较低和罕见的非同义变体，以及它们与常见复杂性状的关联，如心血管疾病，癌症，身体组成，血脂，葡萄糖，胰岛素和多种族人群中的许多其他结果。具体而言，我们建议使用新开发的ExomeChip基因分型平台，增加额外的内容，重点关注祖先的多样性和非编码区的推定调控元件。该平台具有很高的成本效益，将提供约350，000种变异的基因分型数据，等位基因频率低至0.1%。大多数这些低频变异既没有基因分型，也没有很好地标记现有的GWAS阵列。我们将在来自妇女健康倡议（WHI）的血统多样化人群中使用这种ExomeChip，包括非洲裔美国人（n= 7，510），西班牙裔美国人（n= 5，394）和美洲原住民（n=596）。这些数据将与来自正在进行的WHI研究的23，303名欧洲裔美国人和3，631名非洲裔美国人的ExomeChip基因型和外显子组测序数据相结合，总共有40，434名WHI参与者。这一资源将使我们能够调查低频率和罕见的遗传变异与具有公共卫生重要性的复杂疾病之间的关系，以及与精心策划的中间性状和WHI中可用的4，800多个表型变量之间的关系。我们将开发新的方法，并将其应用于这一丰富的资源中，以估计遗传力，并确定多种表型（多效性）和基因-环境相互作用的变异的影响，这是由我们对常见变异的第1页发现所激发的。通过这些努力，我们希望确定多个易感基因座，这些基因座可以更好地量化遗传变异解释的复杂疾病中的变异比例，确定人群特异性基因座，并提供对共享分子途径的见解，这些分子途径将更有效地指导多样化美国人群的后续预防和治疗策略。所有基因型和相关表型数据将通过数据库（如dbGaP）和WHI系统的一部分提供，为科学界建立资源。

DESCRIPTION (provided by applicant): In the current PAGE study (PAGE 1) we investigated many genetic loci identified through genome-wide association studies (GWAS) in ancestrally diverse populations, and successfully generalized and fine-mapped many GWAS loci from studies of European-descent populations. These successes support extending the genomic search to less frequent and rare variants, which have not been captured in GWAS, but represent the largest fraction of genetic variation in the genome and contribute to the heritabilit of many complex traits. Most GWAS have been conducted in Europeans; yet studies investigating the impact of genetic risk factors, including low frequency variants, on common complex traits in diverse populations are needed including understudied US minorities having high burden of disease. The goal of this project is to comprehensively investigate less frequent and rare non-synonymous variants across the protein coding regions of the genome, i.e. the "exome", and their associations with common complex traits, such as cardiovascular disease, cancer, body composition, blood lipids, glucose, insulin, and many other outcomes in a multi-ethnic population. Specifically, we propose to use a newly developed ExomeChip genotyping platform, augmented with additional content focused on ancestral diversity and putative regulatory elements in non-coding regions. This platform is highly cost-efficient and will provide genotyping data on about 350,000 variants with allele frequencies as low as 0.1%. Most of these low frequency variants are neither genotyped nor well tagged on existing GWAS arrays. We will use this ExomeChip in an ancestrally diverse population including African Americans (n=7,510), Hispanics (n=5,394) and Native Americans (n=596) from the Women's Health Initiative (WHI). These data will be combined with ExomeChip genotypes and exome sequencing data from 23,303 European Americans and 3,631 African Americans from ongoing WHI studies, for a total of 40,434 WHI participants. This resource will permit us to investigate relationships between low frequency and rare genetic variants with complex diseases of public health importance as well as with well-curated intermediate traits and over 4,800 phenotypic variables available in the WHI. We will develop new methods and apply them in this rich resource to estimate heritability and to identify effects of variants across multiple phenotypes (pleiotropy) and gene-environment interaction which are motivated by our PAGE 1 findings for common variants. Through these efforts, we expect to identify multiple susceptibility loci that may better quantify the proportion of variation in complex diseases explained by genetic variants, identify population-specific loci and provide insights into shared molecular pathways that will more efficiently direct subsequent prevention and treatment strategies in the diverse US population. All genotype and associated phenotypic data will be made publically available through databases, such as dbGaP and as part of the WHI system, building a resource for the scientific community.