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.
