Vaginal swabs can be used to predict the likelihood of preterm birth

We often do not know the causes of preterm birth, but analysis of metabolic substances in the vaginal microbiome can help predict the risk of preterm birth.

Certain metabolic substances in the vagina can predict whether a baby will be born prematurely, which is one of the leading causes of newborn death. Testing the vaginal microbiome during pregnancy can help healthcare professionals identify and manage high-risk pregnancies.

Tal Korem of Columbia University in New York and colleagues studied 232 vaginal swabs collected during the second trimester of pregnancy, 80 of which were obtained during preterm pregnancies. About 75 percent of the samples came from people who self-identified as black, a group disproportionately affected by preterm birth in the US.

Previous studies have identified the involvement of the vaginal microbiome in preterm birth, but unlike previous work, Korem and colleagues identified both microbes and metabolites in each sample. Metabolites are small substances formed from the breakdown of foods, drugs, or other chemicals. The team used this data to train machine learning models to predict whether a pregnancy will end in preterm birth, and found that certain metabolites, but not microbes, have the strongest association with preterm birth.

The model using data on metabolites and race had a 78 percent chance of correctly determining whether the sample was taken from a woman whose pregnancy ended in preterm labor or not, while the model using data on microbes, race and other clinical factors, had a 59 percent chance. cent chance.

Remarkably, many of the metabolites associated with preterm birth were not created by microbes or humans, Corem says. “They come from an outside source,” he says. Although further analysis is needed to determine the source, some of these metabolites, such as ethyl glucoside and EDTA, are present in some cosmetic and hygiene products.

“This is far from proof,” says Korem, noting that these results are only association and do not prove causation. As such, no recommendations can be made for avoiding certain foods. “It’s very preliminary, but we sort of raise a flag and say, look, there’s something fishy here that we need to look into,” he says.

“This study, because it’s really focused on recruiting black women, showed the underrepresented very well,” says Kristin Metz of the Feinstein Institute for Medical Research in New York. However, because the microbiome can change depending on various factors, such as environmental exposure, the model can give different results for samples taken from the same person on different days, she says.

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