LC-MS/MS based untargeted lipidomics uncovers lipid signatures of late-onset preeclampsia.

The mechanisms underlying late-onset preeclampsia (LOPE) remain unknown. Metabolic disturbances have been implicated as a primary factor in LOPE development. Lipids have been shown to have great clinical value in recent years. This study aimed to use lipidomics to provide evidence for the etiology and potential therapeutic approaches for LOPE. Twenty patients with LOPE and 20 healthy controls were enrolled in this study. Placental lipidomic data were acquired using liquid chromatographymass spectrometry (LC-MS/MS), and the data were analyzed by weighted gene correlation network analysis (WGCNA) and statistical methods. Of 1508 identified lipids, 226 were differentially expressed between the LOPE and control groups. In the LOPE group, the abundance of most unsaturated triglycerides (TG) increased, whereas that of other lipids, including phosphatidylcholine (PC), sphingomyelin, and phosphatidylserine (PS) increased. The WGCNA implied that the correlation network module of lipids was highly related to clinical traits. Pathway analysis revealed that these dysregulated lipids are closely related to glycerophospholipid metabolism. Lipidomics may help identify the pathogenesis underlying placental dysfunction in LOPE patients and provide potential therapeutic targets in the future.