A Multi-Omic Platform for Polycystic Ovary Syndrome Characterization and Management

项目总结/摘要 多囊卵巢综合征（PCOS）是女性最常见的内分泌疾病， 生育年龄由于多囊卵巢综合征的复杂性，诊断往往被推迟， 治疗和自我管理有限。随着高通量领域的最新发展，接下来- 发电和代谢组学技术，现在有一个独特的机会，利用成本- 有效的多组学方法来研究PCOS患者。 在本申请中，我们建议应用这些技术来检查患有PCOS的妇女， 开发一个具有成本效益、可扩展、集成和高度准确的平台。我们的多- 组学平台（FemBio）将整合患者的医疗记录，基因组学，微生物组学 （鸟枪宏基因组学）和代谢组学，以创建妇女的分子概况， 没有PCOS这种方法有可能提供一个更全面的 多囊卵巢综合征的特征，导致改进的诊断标志物的鉴定， 允许发现新的治疗靶点。此外，我们提出了一个前瞻性的 观察性队列研究，包括全基因组测序，鸟枪宏基因组学 肠道微生物组测序、粪便代谢组学、血清和尿液激素水平，以及 PCOS患者和健康对照组的临床指标。 该平台（FemBio）将使最新的分子测定，多功能， 组学量化和计算建模的一般公众，这是目前 缺乏反过来，这将改善多囊卵巢综合征的特征，长期管理， 并为数百万患有这种疾病的妇女提供潜在的新治疗选择， 疾病，以及作为一个大的，注释的多组学数据集，可以帮助PCOS领域 更广泛地说。

Project Summary/Abstract Polycystic ovarian syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Due to the complex nature of PCOS, diagnosis is often delayed and options for treatment and self-management are limited. With recent developments in high-throughput, next- generation and metabolomics technologies, there is now a unique opportunity to utilize a cost- effective, multi-omic approach to study individuals with PCOS. In this application, we propose to apply these technologies to examine women with PCOS, developing a platform that is cost-effective, scalable, integrative, and highly accurate. Our multi- omic platform (FemBio) will integrate patient’s medical records, genomics, microbiome (shotgun metagenomics), and metabolomics to create a molecular profile of women with and without PCOS. This approach has the potential to provide a more comprehensive characterization of PCOS, to lead to the identification of improved diagnostic markers, and to allow for the discovery of novel targets for treatment. Moreover, we propose a prospective observational cohort study including whole genome sequencing, shotgun metagenomic sequencing of the gut microbiome, fecal metabolomics, serum and urine hormone levels, and clinical indices in a sample of individuals with PCOS and a healthy control group. This platform (FemBio) will enable broader accessibility to the latest in molecular assays, multi- omic quantification, and computational modeling for the general public, which currently is lacking. In turn, this will improve options for PCOS characterization, long-term management, and open potentially new treatment options for the millions of women suffering from this disorder, as well as serve as a large, annotated multi-omic data set that can help the PCOS field more broadly.