Serum metabolites as diagnostic biomarkers for preterm labor: a metabolomics-based study

Abstract

Background: Preterm labor is a common high-risk condition during pregnancy, but current diagnostic approaches, such as cervical length measurement and uterine contraction monitoring, lack sufficient specificity and sensitivity. This study aims to explore potential biomarkers for threatened preterm labor using untargeted metabolomics, providing novel indicators to improve clinical diagnosis. Methods: A total of 46 pregnant women from Jiangxi Maternal and Child Health Hospital were retrospectively enrolled in case–control study and divided into a preterm birth group (n = 23) and a control group (n = 23) based on gestational age. Serum metabolic profiles were analyzed using untargeted metabolomics. Differential metabolites were identified via Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) and P-value screening. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to explore their biological relevance. Logistic regression and Receiver Operating Characteristic (ROC) curve analysis were applied to evaluate potential biomarkers for threatened preterm labor. Results: Using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), key metabolites associated with preterm birth were identified, including cis-9-palmitoleic acid (AUC = 0.830), 2-amino-1-phenylethanol (AUC = 0.718), and phenylalanine (AUC = 0.708), as shown by ROC curves. These metabolites were significantly elevated in the preterm group and showed good diagnostic potential (AUC > 0.5). Conclusions: Several serum metabolites were identified as potential biomarkers for threatened preterm labor, defined by regular uterine contractions, cervical changes, and abnormal vaginal discharge before 37 weeks. These findings may aid in the early diagnosis of preterm birth.