RSS feed source: National Science Foundation
Each year, preeclampsia—a life-threatening pregnancy complication—affects nearly 1 in 25 expectant mothers in the United States. Emerging suddenly after 20 weeks of pregnancy, it can lead to dangerously high blood pressure, premature birth, and long-term health issues for both mother and baby. Despite its severity, the root causes of preeclampsia remain poorly understood, and treatment options are limited.
Currently, the only effective treatment for preeclampsia is early delivery of the placenta, which often leads to premature birth and associated health risks for the baby. While researchers know the placenta plays a central role in the disease, the exact causes of its dysfunction remain unclear. This lack of understanding makes preeclampsia difficult to predict, prevent, or treat effectively.
Researchers at UC San Diego are tackling these challenges with help from NSF-supported computational resources. The team leveraged advanced computing systems like the San Diego Supercomputer Center’s Expanse to conduct large-scale RNA sequencing analysis to compare placental tissue from healthy and preeclamptic pregnancies—processing terabytes of next-generation sequencing data to identify genes that behave differently in the disease.
Expanse also enabled the team to develop a model system of preeclampsia using induced pluripotent stem cells (iPSCs), which allows scientists to recreate the disease in the lab and observe how stress conditions like low oxygen affect placental development. By replicating these abnormal conditions, the team identified biological pathways—like inflammation and
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