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

项目 2 - 使用综合基因组、细胞和表型组方法破译人类不孕症常见形式的分子驱动因素

• 批准号: 10613360
• 负责人: Cecilia M. Lindgren
• 金额: $ 24.03万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-10 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10613360
• 关键词: Acceleration; Address; Affect; Alleles; Assisted Reproductive Technology; Bioinformatics; Biological; Biological Assay; Biological Process; Biology; Cell model; Chromosome Mapping; Collaborations; Complex; Couples; Data; Development; Endocrine System Diseases; Evaluation; Female infertility; Fertility; GNRH1 gene; Gene Expression; General Hospitals; Genes; Genetic; Genetic Variation; Genetic study; Genomics; Gonadal Steroid Hormones; Health; Hormonal; Human; Human Genetics; Individual; Infertility; Infertility study; Investigation; Knowledge; Male Infertility; Maps; Massachusetts; Mendelian randomization; Meta-Analysis; Methods; Modeling; Molecular; Morbidity - disease rate; Neurons; Overlapping Genes; Pathway Analysis; Pathway interactions; Pattern; Phenotype; Pituitary Gland; Population; Protocols documentation; Puberty; Rare Diseases; Reproductive Health; Reproductive Medicine; Risk; Risk Factors; Sampling; Series; Structure; Techniques; Technology; Validation; Variant; Visualization; biobank; brain magnetic resonance imaging; cell type; computerized tools; cost; data access; genetic analysis; genetic architecture; genetic association; genetic linkage; genetic variant; genome wide association study; genome-wide; in silico; infertility treatment; novel; olfactory bulb; phenome; phenomics; pleiotropism; protein protein interaction; reproductive; trait

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.

项目摘要 不育是一种常见的状况，影响了十分之一的夫妻试图受孕，以及 全球管理不育症超过180亿美元。我们对 不育的基本机制和风险因素，这些差距阻碍了目标的发展 解决不孕症根本原因的治疗方法。项目2将通过进行人类遗传来填补这些空白 研究不孕症和相关生殖特征的前所未有的量表的研究。通过与之合作 全球大型生物库，我们将访问来自超过1800万个人的数据，以识别遗传变异 与女性和男性不育症以及与许多与生育有关的风险有关 特征，包括性激素浓度，青春期发作，垂体和嗅球大小（AIM 1）。 然后，我们将使用最先进的计算方法来查明特定变体，基因，途径， 以及影响这些条件和特征的细胞类型（AIM 2）。这些方法包括精细映射， 跨研究的途径分析和遗传关联数据的相交，它们将被数据助长 从项目2，AIM 1以及有关与罕见不孕条件相关的遗传变异的数据 项目1，有关核心产生的基因表达的数据，以及有关遗传的大量公开数据 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。然后我们会 整合所有这些发现，以了解AIM 1中研究的不育症和生殖特征如何 其他，在项目1中具有罕见的不育条件，以及一般的生殖和非生殖健康 （目标3）。全球整个关联研究将分析大量表型，以揭示新的表型 研究研究的遗传变异的关联，对多效性的研究将确定在多大程度上 这些条件和特征重叠的遗传原因，并将使用孟德尔随机化技术 推断因果关系。通过利用大规模人遗传学的力量，该项目将导致一个 对生育和不育的生物学的全面了解，确定生育治疗的靶标，以及 揭示生殖健康影响整体健康的途径。