The interaction of basal risk, pharmacologic ovulation induction, pregnancy and delivery on hemostatic balance

妊娠是一个血液学悖论。尽管出血是产妇死亡的主要原因 在世界范围内，妊娠是一种被充分描述的高凝状态， 妊娠期和产褥期观察到的血栓栓塞事件。这种高凝状态 与性激素水平升高有关。然而，绝大多数孕妇（99.9%）没有 妊娠或产后期间发生血栓形成事件，尽管有出血并发症， 大约10%的妇女存在先兆子痫（及其相关的血液学疾病）。此外，在 接受药物促排卵的妇女，在妊娠早期血栓形成的风险增加， 至10倍，但绝大多数（99.6%）维持适当的止血平衡， 临床并发症。在本提案中，我们将确定补偿机制， 血栓形成和建立数学模型，联合收割机这些机制的见解与个人的具体 临床参数和选择生物标志物值来预测整个妊娠期异常止血的风险。R61： 识别并定量评估可能防止血栓形成事件的止血途径 以及药物诱导排卵和围产期事件如何影响这些途径。我们将收集 数据，以建立一个自然的历史有关的性激素的影响，在怀孕期间。在一个队列中， 自然妊娠将从孕前到孕早期进行纵向评估， 队列，将从妊娠第三个月到产后几个月随访妊娠，比较剖宫产 阴道分娩的分娩和非分娩。数据将包括临床和人体测量参数， 止血平衡（血栓稳定性）的动态评估，生物标志物测量捕获变化 妊娠前凝血/抗凝/纤溶成分和途径，以及炎症标志物 和细胞激活。计算建模评估凝血剂、抗凝剂和 每个个体的纤维蛋白溶解蛋白质组将为观察到的止血功能改变提供机制性见解。 平衡R33：1）开发整合临床数据、动态测量和生物标志物数据的模型， R61阶段，以确定保护免受血栓形成的机制，并预测个体风险， 最常见的临床问题，包括辅助妊娠期间植入失败和出血 2）启动一项对辅助和自然妊娠的纵向研究，其中每个人都 随后从孕前到产后期间使用动态和静态测定（从R61阶段）， 似乎对性激素浓度的变化最敏感; 3）成熟并验证初步的 使用纵向研究数据的模型。评价个体特异性止血特征的预测模型 将推进到监测妊娠和评估风险的新方法，以增加 治疗干预。

Pregnancy presents a hematologic paradox. Despite hemorrhage being the leading cause of maternal mortality worldwide, pregnancy is a well described hypercoaguable state, conferring a significant increase in clinical thromboembolic events observed during pregnancy and the puerperium. This hypercoagulable state appears linked to increases in sex hormone levels. However, the vast majority of pregnant women (99.9%) do not have a thrombotic event during pregnancy or the post-partum period, although bleeding complications and preeclampsia (with its associated hematologic disorders) exist in approximately 10% of women. Additionally, in women undergoing pharmacologic ovulation induction the risk of thrombosis in the first trimester is increased up to 10-fold, but here too the vast majority (99.6%) maintain an appropriate hemostatic balance and remain free of clinical complications. In this proposal, we will identify compensating mechanisms that confer protection from thrombosis and build mathematical models that combine these mechanistic insights with an individual's specific clinical parameters and select biomarker values to predict risk for aberrant hemostasis across pregnancy. R61: Identify and quantitatively assess the hemostatic pathways in place that may protect against thrombotic events and how pharmacologic ovulation induction and peripartum events may affect these pathways. We will collect data to establish a natural history relevant to sex hormone influence during pregnancy. In one cohort, assisted and natural pregnancy will be longitudinally assessed from pre-pregnancy to the first trimester while in the other cohort, pregnancy will be followed from the 3rd trimester to several months postpartum comparing cesarean delivery with and without labor with vaginal delivery. Data will include clinical and anthropometric parameters, dynamic assessments of hemostatic balance (thrombus stability), biomarker measurements capturing alterations in pre-pregnancy coagulant/anticoagulant/fibrinolytic components and pathways, and markers of inflammation and cellular activation. Computational modeling assessing the contributions of the coagulant, anticoagulant and fibrinolytic proteome of each individual will provide mechanistic insights into observed alterations in hemostatic balance. R33: 1) Develop models that integrate clinical data, dynamic measures and biomarker data from the R61 phase to both identify mechanisms that confer protection from thrombosis and to predict individual risk for the most common clinical problems, including failure to implant during assisted pregnancy and hemorrhage during delivery; 2) Initiate a longitudinal study of assisted and natural pregnancy in which each individual is followed from pre-pregnancy into the postpartum period using dynamic and static assays (from R61 phase) that appeared most responsive to the changes in sex hormone concentrations; 3) Mature and validate the preliminary models using the longitudinal study data. Predictive models that evaluate individual-specific hemostatic profiles will be advanced to novel approaches of monitoring pregnancy and evaluating risk to enhance opprtunity for therapeutic interventions.