Primary Ovarian Insufficiency: Etiology and Comorbid Disease

原发性卵巢功能不全（POI）是卵巢功能不全的一部分，从不孕症到不孕症， 高FSH水平导致45岁之前的早期绝经，影响5-10%的女性。虽然已经 流行病学研究表明，患有POI的女性患有心血管疾病、骨质疏松症和 死亡率的增加、共病的范围以及POI与死亡率之间的关系并不 清楚此外，POI的遗传基础可能使妇女易患以前未被发现的疾病。 定义，并可能与影响男性生育力的基因重叠。我们将研究POI的家庭隔离， 男性不育症、共病和死亡率来揭示这些关系。然后我们会将独特的DNA 犹他州大学开发的一种序列分析软件，用于发现家族性疾病中的新基因突变。 POI病例，并确定它们是否也与共病分离。具体目标1确定 犹他州人口数据库（美国最广泛的家谱数据库）中的POI家族性病例。 遗传模式，家庭规模和交叉与男性不育症将进行检查。具体目标2 检查家族性POI的相关表型、共病疾病和死亡率，以确定其对 整体健康状况，并确定家庭在POI的风险。具体目标3将确定妇女的基因突变 通过全外显子组或全基因组测序，确定这些突变是否与家族性POI有关， 也与共病分离。我们将使用新的软件（pVAAST和Phevor）开发的 犹他州大学和对照组招募了老年健康研究人员，以优先考虑家族性兴趣点的变异。软件 鉴定与POI表型有密切关系的基因中罕见的破坏性变异。变体将 使用三组散发性POI女性（n=269）进行重复。这项工作将生育率作为一个 通过识别与卵巢储备功能下降和POI相关的疾病来确定整体健康的标志。它还 阐明了我们对生殖衰老过渡期遗传学的理解。使用此结果 根据这项建议，我们将能够确定POI女性的疾病风险。相反，我们将使用家族史 和相关疾病，以确定妇女在POI的风险。新的基因突变和途径将告知 软件算法，如Phevor，将使用新的信息来优先考虑下一个发现的变体 世代排序这些算法最终可能被用来预测全基因组测序后的生育能力。 测序或确定其他女性POI的遗传原因。早期识别将带来 保持生育能力的潜力，并为这些妇女创造有针对性的治疗选择。相反，评估 患有POI的女性的共病风险将针对不孕症治疗后的患者进行疾病预防。

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.