A UC San Francisco-led study has for the first time identified genetic variants that predict whether a patient is likely to respond to treatment for preterm birth, a condition that affects 1 in 10 infants born in the United States.
The findings are critical because no medication is available in the U.S. to treat preterm birth. Last year, the Food and Drug Administration (FDA) pulled the only approved therapy to help reduce the likelihood of preterm births, citing ineffectiveness. The drug, a synthetic form of progesterone, was sold under the brand name Makena.
The new research found that pregnant individuals with high levels of mutations in certain genes — specifically those associated with involuntary muscle contraction — were less likely to respond to the treatment. Screening for the mutations could allow doctors to target Makena and other potential medications to those most likely to benefit, the authors suggest.
“This study calls for a precision framework for future drug development,” said the study’s senior author, Jingjing Li, PhD, associate professor in UCSF’s Department of Neurology and the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research. “In addition to understanding drug effects based on population averages, we also need to take into account the drug response of each individual patient and ask why some respond and some don’t.”
The study, which was done in collaboration with Stanford University, appears Jan. 19, 2024, in the journal Science Advances.
New genes associated with preterm birth
Preterm birth — babies born alive prior to 37 weeks of gestation instead of at the standard 40 weeks — is the leading cause of infant mortality and affects some 15 million pregnancies worldwide each year. Preterm birth also leads to a range of long-term health consequences including breathing problems, neurological impairments such as cerebral palsy, developmental disabilities, visual and hearing impairments, heart disease and other chronic illnesses.
To conduct the study, researchers developed a machine-learning framework to analyze genomes of 43,568 patients that had spontaneous preterm births. The approach uncovered genes that had not previously been known to be associated with preterm birth.
They examined mutations in the genes among those who had received the progesterone treatment Makena. The FDA approved the drug in 2011 after a single clinical trial but took it off the market last spring after concluding the drug didn’t work.
Progesterone therapy was the only treatment for recurrent preterm birth over the past decade, and its recent withdrawal by the FDA has left a void in the medication options available for preterm birth patients.”Cheng Wang, PhD
The decision left doctors without an approved medication to prevent preterm births and frustrated those who had found it effective for a subset of their patients. This posed the question: Could there be a genetic reason why progesterone therapy worked for some, but not for others?
The researchers discovered that patients in the group with low levels of mutations in the genes associated with muscle contractions were more likely to respond to Makena, but those with higher levels tended not to respond. About 19% patients in the study group had high mutation levels in those muscle genes, and none of those individuals responded to Makena.
The findings suggest a personalized medicine approach involving genetic screening could lead to successful results in patients without a high burden of those mutations.
“Progesterone therapy was the only treatment for recurrent preterm birth over the past decade, and its recent withdrawal by the FDA has left a void in the medication options available for preterm birth patients,” said the study’s first author, Cheng Wang, PhD, a postdoctoral scholar at UCSF.
“In previous clinical practice, we did see that many patients benefited from progesterone therapy,” Wang said. “We probably should reevaluate its efficacy, if we can identify those who respond positively to the treatment.”
The researchers included a cohort of African American patients in the study to determine whether the findings applied broadly across different races. Black women in the U.S. are almost twice as likely to give birth prematurely than white women.
They found the genetic burden did not vary by race. This suggests the high rate of preterm birth among Black mothers may be due primarily to environmental factors such as elevated stress hormones, health care biases and lack of prenatal care.
A new type of precision medicine
The researchers went beyond that finding to identify new targets and potential therapies to treat preterm birth by screening more than 4,000 compounds. They homed in on 10 predicted to interact with the genes associated with preterm birth.
Many of these therapeutic compounds are already being used to treat cancer and other diseases, which means that these drugs could possibly be repurposed to help prevent preterm labor. A top candidate is the small molecule RKI-1447, a drug that is currently being used to treat cancer, glaucoma and fatty liver disease. Additional study of the potential of these molecules in treating preterm birth is needed.
Funding and disclosures: This work was supported by National Institute of General Medical Sciences (R35GM142983) and the Marcus Program in Precision Medicine Innovation at UCSF. The study was also funded by the March of Dimes Prematurity Research Center at Stanford University School of Medicine, the Stanford Maternal & Child Health Research Institute and the National Institutes of Health (grants HD092316 and HL160018). Li is co-founder and a member of the scientific advisory board of the genomics-based technology company SensOmics Inc.