Using the Exome to Discover Genetic Determinants of Fibroids in African Americans

描述（由申请人提供）：子宫肌瘤影响美国77%的绝经期妇女，每年造成21亿美元的医疗费用。直到最近，研究肌瘤生长的肿瘤组织和细胞培养研究一直是了解肌瘤病理生理学的主要来源。遗传分析提供了一个强大的和具有成本效益的工具，以确定病因和因果因素，特别是因为遗传易感性纤维瘤已经显示从双胞胎研究。高达69%的风险由遗传因素解释。种族差异也支持遗传学在纤维瘤风险中的作用。非裔美国人（AA） 与欧洲裔美国人（EAs）相比，女性具有更早的发病年龄、更多和更大的肌瘤，具有更高的终生发病率。在现有的遗传分析方法中，与全基因组关联研究（GWAS）相比，全外显子组基因分型（WEG）是最具成本效益和效率的，GWAS专注于本身可能不是因果关系的常见变异。在这项研究中，我们将利用一个独特的范德比尔特资源，BioVU DNA数据库。BioVU拥有超过141，221个成人DNA样本与电子病历（EMR）相关联。从BioVU中，我们确定了3，535例AA受试者（612例病例和2，923例对照），他们符合我们严格的入选标准。研究表明，许多患有子宫肌瘤的女性没有症状，如果没有成像，多达51%的女性可能会被错误分类。因此，我们需要对病例和对照组进行盆腔成像。作为机构倡议的一部分，目前正在使用Illumina的外显子组芯片对50，000名BioVU受试者进行基因分型，包括所有AA（2013年夏季完成）。我们的第一个目标是使用逻辑回归（常见变体）和基于基因的等位基因折叠方法（罕见变体），使用AA BioVU受试者（n = 3，535）验证子宫肌瘤的WEG研究，以评估SNP与子宫肌瘤风险的相关性。我们的第二个目标是使用AA BioVU极端纤维瘤病例（n = 75）和对照（n = 75）以50倍重测序外显子组，以发现与纤维瘤风险相关的新编码变体。极端的情况是那些最年轻的肌瘤发病和最大的数量和大小的肌瘤。极端对照组是年龄最大的受试者，没有记录的纤维瘤病史。目标2将使我们能够验证目标1中发现的变异，以及识别基因分型芯片上未包含的新变异。NIH、NICHD、AHRQ和OWHR已将了解子宫肌瘤风险研究的机制作为优先事项。本研究是AAs中规模最大、也是第一个完整的子宫肌瘤外显子组实验。样品和资源的即时可用性使我们能够在R03的预算和时间限制内实现这些R01范围目标。这些目标将使我们能够使用两种不同的方法（WEG和使用极端表型的外显子组重测序）鉴定与肌瘤相关的新变体，并为未来R01检查与不同种族的肌瘤相关的罕见变体奠定基础。我们提出的研究将从根本上改变有关肌瘤的知识，并在理解肌瘤形成机制方面取得突破。

DESCRIPTION (provided by applicant): Uterine fibroids affect 77% of women by menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Until recently, tumor tissu and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis provides a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibrods has already been shown from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics in fibroid risk. African American (AA) women have earlier age-of-onset, more numerous and larger fibroids with a greater lifetime incidence compared to European Americans (EAs). Among existing genetic analysis approaches, whole exome genotyping (WEG) is the most cost-effective and efficient compared to genome-wide association studies (GWAS) that focuses on common variants that may themselves not be causal. In this study, we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU has over 141,221 adult DNA samples linked to electronic medical records (EMR). From BioVU we have identified 3,535 AA subjects (612 cases and 2,923 controls) who meet our stringent inclusion criteria. Studies have shown that many women with fibroids are asymptomatic and without imaging as many as 51% of women may be misclassified. As a result, we have required pelvic imaging for both cases and controls. 50,000 BioVU subjects are currently being genotyped using Illumina's Exome Chip as part of an institutional initiative, including all AAs (completion summer of 2013). Our first aim is to conduc a WEG study of fibroids using AA BioVU subjects (n = 3,535) using logistic regression (common variants) and gene-based allele collapsing approaches (rare variants) to evaluate associations of SNPs with fibroids risk. Our second aim is to resequence exomes at 50X using AA BioVU extreme fibroid cases (n = 75) and controls (n = 75) to discover novel coding variants associated with fibroid risk. Extreme cases are those with youngest fibroid onset and largest number and size of fibroid. Extreme controls are the oldest subjects with no recorded history of fibroids. Aim 2 will allow us to validate variants discovered in Aim 1, as well as to identify nove variants not included on the genotyping chip. The NIH, NICHD, AHRQ, and the OWHR have made understanding the mechanisms underlying fibroid risk research priorities. This study is the largest and first whole exome experiment of fibroid among AAs. Immediate availability of samples and resources allow us to accomplish these R01 scope Aims within the budgetary and time constraints of an R03. These aims will allow us to identify novel variants associated with fibroids using two distinct approaches (WEG and exome resequencing using extreme phenotypes) and will lay the ground work for a future R01 examining rare variants associated with fibroids across racial groups. Our proposed study will fundamentally change knowledge about fibroids and lead to breakthroughs in understanding mechanisms in fibroid formation.