Abstract
Cervicovaginal fluid (CVF) is an excellent specimen for monitoring preterm birth (PTB) as it characterizes cervical metabolites, the vaginal environment, and specific host immune responses. However, extensive lipid analysis of CVF to explain PTB has not been studied. In this study, we performed a systematic analysis combining high-throughput lipid analysis and omics to discover the unique metabolic properties of the cervix. Liquid chromatography-high resolution mass spectrometry successfully detected a total of 190 lipids in the CVF of 30 PTB and 30 term birth (TB) pregnant women. The whole lipidomics dataset analyzed by combining multivariate and univariate statistical analysis revealed 35 lipid biomarkers, including phospholipids and sphingolipids. Remarkably, sphingomyelin, which plays a physiologically essential role in sphingolipids, was significantly downregulated in PTB. Metabolic pathway study provides a close relationship between vaginal microbial organization and cell membrane formation, further supporting the robustness of our findings. Sphingolipids and phospholipids, which were determined to be important lipids for predicting PTB in our study, showed a high value of receiver operating characteristic (ROC) curve >0.7, indicating that a lipid diagnostic test and understanding the mechanism of lipids is highly related to the vaginal microbiome. Therefore, our result has high potential as a predictor of PTB.