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，我们研究了许多通过全基因组关联研究（GWAS）在祖先多样化人群中鉴定的遗传位点，并成功地从欧洲后裔人群的研究中归纳和精细定位了许多GWAS位点。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中没有被捕获，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是在欧洲进行的；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特征的影响，包括未充分研究的美国高疾病负担少数民族。该项目的目标是全面研究基因组蛋白质编码区域（即“外显子组”）中不太常见和罕见的非同义变异，以及它们与常见复杂特征（如心血管疾病、癌症、身体成分、血脂、葡萄糖、胰岛素和多种族人群中的许多其他结果）的关联。具体来说，我们建议使用新开发的ExomeChip基因分型平台，增加额外的内容，重点关注祖先多样性和非编码区推定的调控元件。该平台具有很高的成本效益，将提供约35万个等位基因频率低至0.1%的变异的基因分型数据。大多数这些低频变异既没有基因分型，也没有很好地标记在现有的GWAS阵列上。我们将在来自妇女健康倡议（WHI）的不同祖先人群中使用这种ExomeChip，包括非洲裔美国人（n= 7510）、西班牙裔美国人（n= 5394）和美洲原住民（n=596）。这些数据将与正在进行的WHI研究中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研究低频和罕见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世界卫生组织中可用的4800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，并识别跨多种表型（多效性）和基因-环境相互作用的变异的影响，这些影响是由我们对常见变异的发现所激发的。通过这些努力，我们期望确定多个易感位点，从而更好地量化由遗传变异解释的复杂疾病的变异比例，确定人群特异性位点，并提供对共享分子途径的见解，从而更有效地指导不同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dbGaP等数据库公开提供，并作为WHI系统的一部分，为科学界建立一个资源。

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.