Preeclampsia is a multi-system hypertensive disorder of pregnancy affecting 2-8 % of deliveries in the US. It is characterized by variable degrees of maternal symptoms including elevated blood pressure, proteinuria and fetal growth retardation. Preeclampsia is one of the most common causes of fetal and maternal morbidity and mortality worldwide. There is currently no effective intervention for preeclampsia short of delivery of the fetus, thus preeclampsia is a leading cause of premature birth. Large-scale molecular profiling technologies permit the identification of disease mechanisms and understanding of underlying cellular processes. It is now known that nearly all tissues and cell types release vesicles from their plasma membrane. The contents of extracellular vesicles, including both mRNA and miRNA, are tissue specific, can be translated into proteins by target cells and that those RNAs can be functionally transferred to recipient cells and lead to alterations in downstream signaling. We hypothesize that the mechanism for severe preeclampsia can be revealed by comparing the transcript profile of the extracellular vesicles from the whole blood of women diagnosed with the disorder prior to delivery of the fetus versus gestational age matched normotensive women not in labor. We will use innovative bioinformatics techniques to analyze differential expression and to deconstruct the transcription profiles of the exosomal cargo into the contribution from their tissues of origin. Identification of the transcript profiles in these extracellular vesicles will provide insights into the mechanisms and pathogenesis of severe preeclampsia and lead to new strategies for treatment, prediction and prevention.
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