Despite decades of investigation, we cannot predict, prevent, or treat preeclampsia, other than by delivery of the placenta. There have been several multicenter prediction studies like the Combined Anti-oxidant Prevention and Prediction Study (CAPPS) performed by the NICHD (Myatt, 2012) that measured a wide variety of biomarkers and failed to provide a model for the early prediction of preeclampsia. The current working hypothesis for these repeated failures is preeclampsia is a heterogeneous syndrome with various etiologies; therefore, no combination of biomarkers will provide early predictive power. However, the preeclampsia syndrome may be further classified into early onset (<34 weeks), late onset, severe, and mild disease. These different groups may have different causes, but the current dogma is severe preeclampsia is related to defective placental invasion; whereas, late onset mild preeclampsia is a due to abnormal maternal endothelial cell activation. The challenge is to develop a new approach to identify predictive biomarkers. Recently, there has been a growing interest in placental and maternal extracellular vesicles (EVs) to determine if these complex lipid-based spheres involved in inter-cellular communication may offer clues to the early pathophysiology of preeclampsia and targets for early disease detection. These submicron-sized EVs are released by the placenta, endothelial cells, platelets, and numerous other sources into maternal blood. Most of these vesicles are ~100nm sized exosomes that retain cell-specific plasma membrane surface markers. Their concentration and relative size distribution may provide clinical predictive power. We have developed an innovative approach to identify cell- and size- specific EVs in maternal plasma by multiplex high resolution flow cytometry (HRFC). We have shown the reproducibility of this methodology within and between human plasma samples on a number of specifically designed BD high resolution flow cytometers (eg, FACSAria Fusion, upgraded Canto II), which are now commercially available. We now propose to test the predictive power of this new approach to identify women at risk for preeclampsia. We will use the well-characterized NICHD banked maternal plasma samples from the CAPPS study, which were uniformly collected and are linked to patient metrics, a range of biomarkers, and outcomes. Our overarching hypothesis is that we can identify EVs from different cell types in maternal plasma and that the type and number of these EVs per ml of plasma will differ between normotensive controls and women who develop severe preeclampsia (early or late onset), or mild late onset preeclampsia. We will utilize maternal plasma collected at 32, 24, and 11 weeks' gestation to measure the number of placental (PLAP+, HLA-G/C+, CD56+) and endothelial (CD31+) EVs/ml in triplicate in women previously classified into mild preeclampsia (n=100), severe preeclampsia (n=56), early onset severe preeclampsia (n=18), and controls (n=509). We will compare mean concentrations between groups adjusting for covariates in the model.
We will employ new high resolution flow cytometry (HRFC) technology developed from Human Placenta Project R21 funding to test banked plasma samples that were uniformly collected by the NICHD for the CAPPS study of 174 well-characterized women with preeclampsia (74 severe, 100 mild) and 509 matched controls. HRFC technology can profile cell- and size-specific submicron extracellular vesicles (EVs) released into the blood by the placenta, endothelial cells, or other cell origins. We hypothesize that cell-specific EV numbers/ml of plasma will be significantly different at 32, 24, and 11 weeks gestation in women who develop preeclampsia and show improved predictive value compared with the biomarkers previously tested in the CAPPS study.
