LAUSR

Despite intensive investigation, we still cannot adequately predict, treat, or prevent preeclampsia. We have gained awareness that preeclampsia is a syndrome not a disease and is heterogeneous in its presentation and pathophysiology, which may indicate differing underlying phenotypes, and that the impact extends beyond pregnancy per se. Effects on the fetus and mother extend many years after pregnancy, as evidenced by fetal programming of adult disease and increased risk of the development of maternal cardiovascular disease. The increased occurrence of preeclampsia in women with preexisting risk factors suggests that the stress of pregnancy may expose subclinical vascular disease as opposed to preeclampsia damaging the vasculature. The heterogeneity of preeclampsia has blighted efforts to predict preeclampsia early in gestation and has thwarted success in attempts at therapy with treatments, such as low-dose aspirin or global antioxidants. There is a critical need to identify the phenotypes to enable their specific prediction and treatment. Such studies require considerably larger collections of patients than employed in past and current studies. This does not necessarily imply much larger patient numbers in single studies but can be facilitated by the ability to easily combine many smaller studies. This can be accomplished by agreeing on a priori standardized and harmonized clinical data and biospecimen collection across new studies. Such standards are being established by international groups of investigators. Leadership by international organizations, perhaps adopting a carrot and stick approach, to overcome investigator, institutional and funder reticence toward data sharing is required to ensure adoption of such standards. Future studies should include women in both low- and high-resource settings and employ social media and novel methods for data collection and analysis, including machine learning and artificial intelligence. The goal is to identify the pathophysiology underlying differing preeclampsia phenotypes, their successful prediction with the design, and the implementation of phenotype-specific therapies.