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In breakthrough study, Stanford researchers detect crucial biological signals indicating approaching labor

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Stanford Medicine researchers have found that certain blood markers and immune signals can predict when a pregnant person will undergo labor — a breakthrough study that could narrow the estimated time range for expectant mothers down to a two-week window.

The first-of-its-kind study was published on Wednesday in the Science Translational Magazine Journal, and it establishes a novel method that within a few years could dramatically increase the precision for forecasting labor. 

Currently, obstetricians utilize ultrasound data and count 40 weeks after the first day of a woman’s last menstrual period to devise an estimate for her due date. However, the study’s senior author and associate professor of anesthesiology, perioperative and pain medicine Brice Gaudilliere said that while clinicians are generally accurate in pinpointing how far along a woman is in her pregnancy, they are not as effective when predicting a specific labor date. 

“In a normal pregnancy, women may go into labor from 37 to 42 weeks,” Gaudilliere said, “so there is a five week window of inaccuracy.” 

This wide range has consequences for certain clinical decisions. In the context of preterm labor, which Gaudilliere noted as the number one cause of global child mortality under 5 years of age, there is not a reliable method to ascertain if expectant mothers may enter premature labor 16 weeks before the typical 40 week average.

By formulating a brand new test that works alongside these detected signals, doctors will become more confident in answering the question of whether or not to induce labor, and if it is the best option for the baby to be delivered prematurely or wait until full term.

Up next for the research team is recruiting more volunteers from medical research groups across the globe, including in countries like Bangladesh, Pakistan and Tanzania. With the amount of pregnant women going into natural labor each year, these studies should be performed fairly quickly — and could save lives.

“We need a lot of patients, so through these internal collaborations, we are increasing the number of patients that we can sample and enroll,” Gaudilliere said.

To conduct the study, researchers recruited a total of 63 women, who each provided regular blood samples throughout the duration of their pregnancies. The two-year-long study was supported by Stanford’s Prematurity Research Center (PRC), a transdisciplinary effort with university research faculty and staff working in tandem to discover “novel approaches for identifying high risk pregnancies and preventing preterm birth,” wrote David Stevenson MD ’71, pediatrics professor and PRC director in an email. Stevenson is listed as an author on the study.

In order to find a more accurate prediction tool separate from gestational age estimates, the research team developed machine learning algorithms which aggregated multiple measurements extracted from metabolites, proteins and immune cell features from a set of 53 women who experienced spontaneous labor, according to Gaudilliere and Ina Stelzer, the study’s lead author and postdoctoral fellow in anesthesiology, perioperative and pain medicine. Upon completion, the team then included an additional 10 women to validate the process. 

There, in the third trimester of the women’s pregnancies, Stelzer and her colleagues noticed an evident shift in hormone, blood clotting and immune signalling levels. This change usually happened two to four weeks before labor, when the expectant mother “transitions [from a ‘progressing pregnancy’] to a ‘pre-labor’ phase.” 

The top predictive marker that their models found was the regulatory immune protein IL-1R4, which helps inhibit inflammation. The prevalence of this protein sharply increases when a person enters pre-labor, perhaps to act as a “counterbalance to the inflammation that a woman experiences when she is in acute labor,” Stelzer said. 

In addition, Stelzer highlighted several significant observations her team noticed alongside the buildup of IL-1R4. Other proteins prominent in the placenta and blood clotting factors increased, while hormones relating to the creation of new blood vessels decreased — an indication of a mature placenta. 

“We saw pregnancy-related hormones, like prodestrol and cortisol, really increase,” she said. “What was shown here was that these factors are tightly linked with the onset of labor, and increasingly ramp up until delivery.” 

According to Stevenson, the data compiled will accelerate development on more definite estimation methods, writing in an email that these findings could lead to tests “with much greater accuracy and allow better planning for parturition.” 

Since the participants were registered at the School of Medicine, Stelzer said that the demographics reflect the Bay Area population, with an average age of 30 years old and Asian and White volunteers making up the majority of participants.

For future cohorts, Gaudilliere and Stelzer plan on including Black, Latinx and other ethnic groups not yet covered. Furthermore, they say that people outside of North America — Europe, Africa and Asia — will be sourced to validate current findings. Subsequent steps will be to reduce their model to just a dozen factors that would be clinically measurable as more patients are included in further research during the next couple years.

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Vol. 260 Academics Desk Editor
Tom Quach '24 serves as the Academics Desk Editor for Vol. 260 and previously covered startups for The Daily's SciTech section. Tom also serves as Account Manager for The Daily's Marketing Team. He's from San Francisco, CA, and enjoys biking and watching Stars Wars on his spare time. Contact him at tquach 'at' stanforddaily.com.