eMB: Collaborative Research: Stochasticity in ovarian aging and biotechnologies for menopause delay

该项目旨在(1)促进对卵巢衰老的了解，(2)优化旨在延迟卵巢“用完卵子”和停止功能(更年期)的技术。支持这两个目标的一个关键假设是，数学和统计学的随机性理论可以解开围绕卵巢功能和功能终止的长期谜团。在一个例子中，尽管女性出生时有大约100万个原始卵泡(包含卵子的基本生殖单位)，但她们在成年后只会排卵几百个卵子。因此，哺乳动物的卵巢有时被称为“浪费”。通过开发与生物学实验紧密结合的数学模型和理论，该项目试图解释卵巢生物学的这一特点和其他令人困惑的特征。此外，更年期给妇女带来了许多具有挑战性的症状和健康后果。随着更年期的临近，心血管健康、骨密度、肌肉质量、身体脂肪组成和其他指标都会恶化。这导致了最近对旨在推迟更年期的药理生物技术的兴趣和投资的激增。然而，目前还没有理论来预测这种干预措施将如何影响更年期的时间。这个项目旨在发展这样一个理论，它将通过生物实验来指导、修改和验证。在数学上，这个建议试图发展非独立同分布(IID)随机变量的极值理论。这样的理论将构成随机学理论的重大进步，并立即在科学的广泛领域得到应用。极值理论处理概率分布尾部的极端事件。这种统计上的“异常值”对卵巢生物学至关重要，因为卵巢健康的寿命取决于原始卵泡生长激活的最后十分之几个百分点。虽然对于IID情形有经典的结果，但对于非IID随机变量的极值理论是非常有限的。从生物学上讲，该提案包含了解决该领域一个非常长期存在的问题的创新方法：如何选择单个休眠的原始卵泡进行生长激活，而大多数卵泡长期处于休眠状态？如果得到证实，这一提议的假设将改变我们对卵巢老化的理解，包括绝经过渡的里程碑式阶段和更年期。虽然随机性经常被视为生理学上的障碍，但这项工作可以帮助我们确定随机过程如何发挥作用，以确保健康、可靠的女性生殖衰老。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to (1) advance the understanding of ovarian aging and (2) optimize technologies designed to delay when ovaries "run out of eggs" and stop functioning (menopause). A key hypothesis underpinning both of these aims is that mathematical and statistical theories of randomness can unlock longstanding mysteries surrounding ovarian function and cessation of function. In one example, even though women are born with around one million primordial follicles (the basic reproductive units that contain eggs), they will only ovulate a few hundred eggs during adulthood. For this reason, ovaries in mammals are sometimes called "wasteful." By developing mathematical models and theories that are closely integrated with biological experiments, this project seeks to explain this and other perplexing features of ovarian biology. In addition, menopause presents women with a number of challenging symptoms and health consequences. Cardiovascular health, bone density, muscle mass, body fat composition, and other measures all worsen as menopause approaches. This has led to a recent surge of interest and investment in pharmacological biotechnologies which aim to delay menopause. However, there is currently no theory to predict how such interventions will affect menopause timing. This project aims to develop such a theory, which will be guided, modified, and validated by biological experiments.Mathematically, this proposal seeks to develop extreme value theory for random variables which are not independent and identically distributed (iid). Such a theory would constitute a major advance in stochastics theory and find immediate application in a wide range of areas of science. Extreme value theory deals with extreme events in the tails of probability distributions. Such statistical "outliers" are critical to ovarian biology because the lifespan of ovarian health depends on the last few tenths of a percent of primordial follicles to growth activate. While there are classical results for the iid case, extreme value theory for non-iid random variables is severely limited. Biologically, the proposal contains innovative approaches to address a very long-standing problem in the field: how are individual dormant primordial follicles selected for growth activation while the majority remain dormant over long periods of time? If validated, the hypotheses of this proposal would transform our understanding of ovarian aging, including the landmark stages of the menopausal transition, and menopause. Though stochasticity is often viewed as an obstacle in physiology, this work can help us to determine how random processes function to ensure robust, reliable female reproductive aging.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.