Primary Ovarian Insufficiency: Etiology and Comorbid Disease

原发性卵巢功能不全(POI)是一系列卵巢功能障碍的一部分，包括不孕不育和 高FSH水平至45岁前绝经早期，影响5%-10%的女性。虽然它一直是 流行病学研究表明POI妇女患有心血管疾病、骨质疏松症和 死亡率的增加、并存疾病的广度以及POI和死亡率之间的关系 安全。此外，POI的基因基础可能使女性更容易患上以前没有发生过的疾病 被定义并可能与影响男性生育能力的基因重叠。我们将研究POI的家庭隔离， 男性不育、并存疾病和死亡率，以揭示这些关系。然后我们将应用独特的DNA 犹他大学开发的序列分析软件用于发现家族性遗传病的新基因突变 POI病例，并确定它们是否也与共病分离。具体目标1确定 美国最广泛的家谱数据库犹他州人口数据库中的POI家族性病例 将检查遗传方式、家庭规模以及与男性不育的交集。具体目标2 检查家族性POI的相关表型、并存疾病和死亡率，以确定其对 总体健康和确定有POI风险的家庭。特定目标3将确定女性的基因突变 通过全外显子组或全基因组测序确定这些突变 也与共病分离。我们将使用新开发的软件(pVAAST和Phevor) 犹他大学和对照组为老年健康招募，以确定家族POI变异的优先顺序。该软件 识别与POI表型密切相关的基因中罕见的破坏性变异。变种将 使用三组患有散发性POI的妇女(n=269)进行复制。这部作品将生育率作为一种 通过识别与卵巢储备减少和POI相关的疾病，作为整体健康的标志。它还 阐明了我们对生殖衰老转变的遗传学的理解。使用来自此的结果 建议，我们将能够确定POI妇女的疾病风险。相反，我们将使用家族历史 以及相关的疾病，以确定POI的风险女性。新的基因突变和途径将告诉我们 Phevor等软件算法将使用新信息来确定Next中发现的变体的优先顺序 世代排序。这些算法最终可能被用来预测全基因组后的生育力 对其他女性的POI进行测序或确定其遗传原因。及早识别将带来 有可能保持生育能力，并为这些妇女创造有针对性的治疗选择。相反，评估 POI妇女的共病风险在不孕症治疗后将针对患者进行疾病预防。

Primary ovarian insufficiency (POI) is part of the continuum of ovarian dysfunction ranging from infertility with a high FSH level to early menopause before age 45 years, and affects 5-10% of women. While it has been suggested in epidemiology studies that women with POI suffer from cardiovascular disease, osteoporosis and increased mortality, the breadth of comorbid disease and the relationship between POI and mortality is not clear. Further, the genetic underpinnings of POI may predispose women to diseases that have not been defined and may overlap with genes affecting male fertility. We will examine the familial segregation of POI, male infertility, comorbid disease and mortality to uncover these relationships. We will then apply unique DNA sequence analysis software developed at the University of Utah to discover novel gene mutations in familial POI cases and determine whether they also segregate with comorbid disease. Specific Aim 1 identifies familial cases of POI in the Utah Population Database, the most extensive genealogical database in the U.S. The inheritance pattern, family size and intersection with male infertility will be examined. Specific Aim 2 examines associated phenotypes, comorbid diseases and mortality in familial POI to determine its effect on overall health and to determine families at risk for POI. Specific Aim 3 will identify genetic mutations in women with familial POI through whole exome or whole genome sequencing and determine whether these mutations also segregate with comorbid disease. We will use novel software (pVAAST and Phevor) developed at the University of Utah and controls recruited for health in old age to prioritize variants in familial POI. The software identifies rare, damaging variants in genes that have a strong relationship to the POI phenotype. Variants will be replicated using three cohorts of women with sporadic POI (n=269). The work addresses fertility as a marker of overall health by identifying diseases associated with decreased ovarian reserve and POI. It also illuminates our understanding of the genetics of the reproductive aging transition. Using results from this proposal, we will be able to determine disease risk in women with POI. Conversely, we will use family history and associated disorders to identify women at risk for POI. New gene mutations and pathways will inform software algorithms such as Phevor, which will use the new information to prioritize variants discovered in next generation sequencing. The algorithms may eventually be used to predict fertility after whole genome sequencing or determine the genetic cause of POI in additional women. Early identification will bring the potential to preserve fertility and create targeted treatment options for these women. Conversely, assessing comorbid disease risk in women with POI will target patients for disease prevention after infertility treatment.