Project 2 - Deciphering the Molecular Drivers of Common Forms of Human Infertility Using Integrative Genomic, Cellular, and Phenomic Approaches

项目摘要 不孕症是一种常见的疾病，影响了十分之一以上试图怀孕的夫妇， 全球治疗不孕症的费用超过180亿美元。在我们的知识中有很大的差距， 不孕症的潜在机制和风险因素，这些差距阻碍了有针对性的发展。 治疗不孕症的根本原因。项目2将填补这些空白， 研究规模空前的研究不孕症和相关的生殖特征。通过与 全球大型生物银行，我们将访问超过1800万人的数据，以确定遗传变异 与女性和男性不育的风险相关，以及与一些生育相关的风险相关， 性状，包括性激素浓度，青春期开始，脑垂体和嗅球的大小（目标1）。 然后，我们将使用最先进的计算方法来确定特定的变异，基因，途径， 以及影响这些条件和性状的细胞类型（目的2）。这些方法包括精细映射， 途径分析，以及跨研究的遗传关联数据的交叉，它们将由数据推动 来自项目2，目标1，以及与罕见不育症相关的遗传变异数据， 项目1，核心产生的基因表达数据，以及广泛的公开可用的基因表达数据。 连锁模式，基因表达，蛋白质-蛋白质相互作用和其他实验发现。然后我们将 整合所有这些发现，以了解目标1中研究的不育和生殖特征如何相互关联， 其他，项目1中罕见的不孕症，一般生殖和非生殖健康 (Aim 3）。全表型关联研究将分析大量表型，以揭示新的表型。 研究的遗传变异的关联，多效性的调查将确定在多大程度上， 这些条件和特征的遗传原因重叠，并将使用孟德尔随机化技术 来推断因果关系通过利用大规模人类遗传学的力量，这个项目将导致一个 全面了解生育和不育的生物学，确定生育治疗的目标， 揭示生殖健康影响整体健康的途径。

PROJECT ABSTRACT Infertility is a common condition that affects over one-tenth of couples attempting to conceive, and the costs of managing infertility exceed 18 billion US dollars worldwide. There are significant gaps in our knowledge of the underlying mechanisms and risk factors for infertility, and these gaps impede the development of targeted treatments that address the root causes of infertility. Project 2 will fill these gaps by conducting human genetic studies of unprecedented scale to study infertility, and related reproductive traits. Through collaborations with large biobanks worldwide, we will access data from over 18 million individuals to identify genetic variants associated with risk for female and male infertility as well as those associated with a number of fertility-related traits, including sex-hormone concentrations, pubertal onset, and pituitary gland and olfactory bulb size (Aim 1). We will then use state-of-the-art computational approaches to pinpoint the specific variants, genes, pathways, and cell types that influence these conditions and traits (Aim 2). These approaches include fine-mapping, pathway analyses, and intersection of genetic association data across studies, and they will be fueled by data from Project 2, Aim 1, as well as data on genetic variants associated with rare infertility conditions identified in Project 1, data on gene expression generated by the Core, as well as extensive publicly available data on genetic linkage patterns, gene expression, protein-protein interactions, and other experimental findings. We will then integrate all these findings to understand how infertility and the reproductive traits studied in Aim 1 relate to each other, with the rare infertility conditions in Project 1, and with general reproductive and non-reproductive health (Aim 3). Phenome-wide association studies will analyze a large number of phenotypes to reveal novel phenotypic associations for the genetic variants studied, investigations of pleiotropy will determine the extent to which the genetic causes of these conditions and traits overlap, and the technique of Mendelian randomization will be used to infer causal relationships. By leveraging the power of large-scale human genetics, this project will lead to a comprehensive understanding of the biology of fertility and infertility, identify targets for fertility treatments, and reveal the pathways by which reproductive health influences overall health.