A Korean research team has discovered new biomarkers that could help predict preterm birth, a leading cause of neonatal death and health complications worldwide.
On Wednesday, Ewha Womans University Mokdong Hospital said that a team led by Professor Kim Young-Ju from the Department of Obstetrics and Gynecology has identified three poly-sialylated glycans in cervicovaginal fluid (CVF) that show strong potential as early indicators of preterm birth.
The study, published in the international journal Scientific Reports, analyzed the site-specific N-glycosylation of proteins found in CVF—fluid located at the cervix and vaginal opening. This fluid contains functional glycoproteins with diverse glycan structures, which play vital roles in immune response, cell signaling, and maintaining pregnancy. However, the potential for these glycans to serve as predictive markers for preterm birth had not been clearly established.
Professor Kim’s team hypothesized that N-linked glycosylation patterns in CVF proteins would differ between women who deliver at full term and those who experience preterm birth. Analyzing samples from 20 pregnancies using advanced N-glycoproteomic techniques, the researchers identified 6,595 N-linked glycopeptides and found 173 glycans that were significantly increased in the preterm group. Notably, this group showed low levels of fucosylation and high levels of sialylation.
Among the findings, three poly-sialylated glycans were consistently expressed in all samples regardless of individual microbiome composition and demonstrated a strong predictive value for preterm birth (AUC = 0.802, p < 0.017). The predictive accuracy improved further when combined with clinical factors such as maternal age and body mass index.
“These poly-sialylated glycans in cervicovaginal fluid show potential as new clinical markers for predicting preterm birth during pregnancy,” said Professor Kim. “Our research proposes a new strategy for developing predictive biomarkers based on glycans in cervicovaginal fluid.”
This research is part of a broader initiative supported by Korea Health Industry Development Institute (KHIDI) under the Korea-U.K. Global Research Collaboration Program. Professor Kim is currently conducting follow-up studies using multi-omics analysis and artificial intelligence on multi-ethnic clinical samples to refine and validate predictive markers for preterm birth.