- Researchers are developing a blood test to help predict whether an expecting mother is at risk for spontaneous preterm delivery based on proteins found in microparticles circulating in the blood.
- The study, a collaboration of NX Prenatal, Brigham and Women's Hospital, the University of Pittsburgh Magee Women's Hospital and Seattle Children's Hospital, evaluated bloom samples from 261 pregnant patients using NX Prenatal's NeXosome platform for exosome isolation.
- In a paper published in the American Journal of Obstetrics & Gynecology, the research team showed that five circulating microparticle proteins found in first trimester blood samples could help predict risk, including among first-time mothers.
In 2017, about one in 10 babies were born premature, before 37 weeks of pregnancy, according to the Centers for Disease Control and Prevention. With preterm birth can come a higher risk of death or long-term problems such as breathing issues or developmental delay.
Preterm labor begins unexpectedly in most cases and the cause is unknown. There is no treatment or prevention.
Microparticles are small cell fragments released by cells sometimes under stress and can transfer peptides, proteins, RNA and DNA from one cell to another. They are being studied for their diagnostic potential as biomarkers in cancer and may play a role in cardiovascular, inflammatory, autoimmune, infectious and other diseases.
The Brigham and Women's researchers and collaborators investigated the role of circulating microparticles in the process of placental implantation. They analyzed multiple associated proteins, finding that a subset could help predict risk of preterm delivery in both first-time mothers and those who had previously given birth.
The team compared blood samples from 87 women who delivered before 35 weeks and 174 women who delivered at term. The patients were the same age and at 10 to 12 weeks' gestation when the samples were taken. The samples were collected from biobanks in Seattle, Boston and Pittsburgh.
NX Prenatal's panels were developed using machine learning statistical techniques. The panel for first-time moms correctly identified preterm delivering patients with specificity (86%) and sensitivity (63%), the company said.
The blood test aims to predict who is at increased risk as well as who is at lower-than-average risk for spontaneous preterm delivery. Study author Thomas McElrath of the Brigham and Women's division of maternal-fetal medicine said the goal is to develop prognostic markers to help make predictions and then tailor treatment to the individual.
The team plans to validate its findings in a larger national data set, further refine the test and include additional risk factors such as maternal characteristics to improve its accuracy. McElrath said the group hopes to use the same testing method to look for prognostic markers of other pregnancy-related conditions such as gestational diabetes.