Longitudinal Evaluation of Ovarian Aging and Cardiovascular Risk

摘要 尽管在预防和治疗心血管疾病(CVD)方面有了重大改进，但日益增长的 人口老龄化表明，心血管疾病将继续构成重大的公共卫生负担。女人是特别的 微血管疾病更常见，传统危险因素可能不能完全识别风险的人群。 妇女的生育史(如月经初潮年龄、月经周期、不孕症、怀孕、更年期)可能 带来了独特的风险，并为新方法提供了机会。我们提出了以妇女为中心的方法 用于早期识别处于危险中的妇女，调查某一年龄段独特的生殖功能丧失 早在其他重要系统失灵之前。尽管这一过程很重要，但人们对此知之甚少 卵巢老化的决定因素或相关因素，或对健康的影响，特别是在不同的人群中。使用 剩余卵母细胞池的可靠生物标志物，我们有一个独特的机会来表征 “卵巢年龄”与加速的卵母细胞丢失的健康影响之间的关系。我们假设一个 风险独立于众所周知的更年期提前和雌激素缺乏的影响。相反，我们 提出共同的潜在细胞衰老机制，由于卵巢的敏感性，首先在卵巢中明显 和更早的死亡，使卵巢成为潜在的躯体健康的窗口。确认关联 卵巢年龄标记物的下降和心血管疾病风险之间的关系将使潜在的高危人群 在传统风险因素发展之前几十年就被识别出来。卵巢老龄化(OVA)队列是最大的 和大多数种族多元化的、以社区为基础的队列，可以用来确定 年轻骑行者卵巢老化的种族/民族和行为决定因素及其与心血管疾病风险的关系 人口。评估卵巢年龄标记物之间的关系(反映既往暴露和遗传 风险)、卵巢衰老率(代表当前暴露)和心血管疾病风险，我们建议：1.确定 卵巢老化的标记物是否与心血管疾病风险增加有关 根据外周血管内皮细胞的测量，年龄/衰老与心血管疾病风险的增加独立相关 功能测试；2.确定卵巢老化是否可以缓和或调节已建立的联系 种族/民族和/或社会/情绪健康与心血管疾病风险之间的关系 社会/情绪健康对心血管疾病风险的差异或影响可能因(调节模型)不同或部分不同。 可归因于(调解模型)卵巢老化；以及3.确定卵巢老化、心血管疾病风险和 出现的时间模式与细胞老化的标志相关：端粒长度和线粒体DNA 外周血白细胞、氧化应激(血浆F2α-异前列腺素)和炎症指标(C反应 蛋白质、白介素6和可溶性细胞间黏附分子-1)。整体影响：我们的小说纵向 评估卵巢和细胞老化标志物作为心血管疾病预测因子的方法可能会带来一种新的方法 确定早期和/或增加心血管疾病风险的妇女，并用于制定新的降低风险战略。

ABSTRACT Despite significant improvements in prevention and treatment of cardiovascular disease (CVD), the growing aging population suggests CVD will continue to pose a significant public health burden. Women are a special group where microvascular disease is more common and traditional risk factors may not fully identify risk. Women's reproductive history (e.g. menarcheal age, menstrual cycles, infertility, pregnancy, menopause) may pose unique risk and suggests an opportunity for new approaches. We propose a women-centered approach for early identification of women at risk that investigates the unique loss of reproductive function at an age long before other vital systems fail. Despite the importance of this process, little is known about the determinants or correlates of ovarian aging, or the health implications, especially in diverse populations. With reliable bio-markers of the remaining oocyte pool available, we have a unique opportunity to characterize the association between “ovarian age” and the health implications of accelerated oocyte loss. We hypothesize a risk independent of the well-known impact of early menopause and estrogen deficiency. Rather, we propose that common underlying cellular aging mechanisms, first evident in the ovary due to its sensitivity and earlier demise, make the ovary a window on underlying somatic health. Confirming an association between a decline in markers of ovarian age and CVD risk would allow a potentially high-risk population to be identified decades before traditional risk factors develop. The Ovarian Aging (OVA) cohort is the largest and most ethnically diverse, community-based cohort available that can be used to determine the race/ethnic and behavioral determinants of ovarian aging and its association with CVD risk in a young cycling population. To assess the relationship between markers of ovarian age (reflecting past exposures and genetic risk), the rate of ovarian aging (representing current exposures) and CVD risk, we propose to: 1. Determine whether markers of ovarian age/aging are associated with increased CVD risk by testing if ovarian age/aging is independently associated with increased CVD risk, as measured by peripheral endothelial function testing; 2. Determine whether ovarian aging may moderate or mediate established associations between race/ethnicity and/or socio/emotional health and CVD risk by examining whether observed race/ethnic disparities, or effects of socio/emotional health, on CVD risk, may vary by (moderation model) or be partially attributable to (mediation model) ovarian aging; and 3. Determine whether ovarian aging, CVD risk, and the temporal pattern of appearance correlate with markers of cellular aging: telomere length and mtDNA in peripheral leukocytes, oxidative stress (plasma F2α-isoprostanes), and indices of inflammation (C-reactive protein, interleukin- 6, and soluble intercellular adhesion molecule-1). Overall Impact: Our novel longitudinal approach to evaluating markers of ovarian and cellular aging as predictors of CVD could lead to a new way to identify women at earlier and/or increased CVD risk and be used to develop new risk-reduction strategies.