Improving pregnancy health: How we can predict challenges sooner

Conditions like preterm birth, preeclampsia, and gestational diabetes impact 45 million women every year across the world. That’s triple the rate of cancer, yet we lack a reliable way to identify patients who are at risk. A team of physicians are working on groundbreaking research into pregnancy-related cell-free RNA (cfRNA) to develop a simple blood test that would enable early detection of these conditions. Drs. Michal Elovitz, Thomas McElrath, and Stephen Quake are working alongside Mirvie on this test, which uses a small blood sample to analyze tens of thousands of molecular transcripts from the mother, baby, and placenta. Made possible with the help of state-of-the-art machine learning, the test aims to help detect conditions earlier and therefore promote better outcomes for mothers and babies.

“The motivation is simple: Our ability to treat patients in obstetrics is behind other fields,” says McElrath, maternal-fetal medicine attending at Brigham and Women’s Hospital and faculty at Harvard Medical School. “If you look at the molecular therapeutics available in oncology or cardiology, big subfields of internal medicine, it’s pretty impressive. That same advancement is not shared by obstetrics.”

This is an excerpt from members-only content. Please log in or become a member to access the full content.