NSF advanced computing accelerates preeclampsia research and potential treatments

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 disrupted blood vessel growth—that play a critical role in the onset of preeclampsia.

These breakthroughs are transforming how scientists think about the disease. By studying over 1,700 placentas (more than 300 from preeclampsia patients), researchers discovered that preeclampsia isn’t a single disorder, but a collection of subtypes with different underlying causes — some tied to maternal blood flow, others to fetal vessel development, or immune system dysfunction. The iPSC models are now being used to further dissect these subtypes, paving the way for personalized detection markers and targeted treatments. The research team is also preparing for future high-throughput drug screening to test therapies for each subtype using their lab-grown placental models.

The broader impacts are profound: Early detection of preeclampsia could prevent complications, save lives, reduce costly preterm births, and improve health outcomes for mothers and babies alike. This research also creates a powerful new platform for studying other placenta-related pregnancy disorders.

The research was enabled by supercomputer allocations from NSF Extreme Science and Engineering Discovery Environment project, which gave way to the NSF Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support program, a national cyberinfrastructure coordinating and support system that connects the research community to advanced computing and data resources supported by the NSF Advanced Computing Systems and Services program.