Lipidomic signatures in maternal blood and placenta: Systematic evidence linking lipid profiles to pregnancy outcomes and fetal growth

Abstract

Introduction: Pregnancy involves profound metabolic adaptations, particularly in lipid metabolism. Disruptions in lipid profiles have been implicated in obstetric complications, yet no systematic synthesis of lipidomic evidence exists across diverse pregnancy outcomes. The primary objective of this review was to identify and synthesize consistent lipid species and lipid classes across studies of maternal and fetal biospecimens, in relation to adverse pregnancy outcomes.The secondary objective was to evaluate the potential predictive and prognostic utility of lipidomic signatures for risk stratification, including their capacity to provide early biomarkers and to inform postpartum metabolic surveillance. Methods: A systematic search of five databases (PubMed, Scopus, EMBASE, Web of Science, Cochrane Library) was conducted up to 2024. Eligible studies involved pregnant or postpartum women undergoing lipidomic analysis by mass spectrometry or nuclear magnetic resonance (NMR), with outcomes including preeclampsia, gestational diabetes (GDM), preterm birth, fetal growth restriction (FGR), and postpartum metabolic risk. Data extraction and quality assessment were performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the Newcastle-Ottawa Scale quality assessment tool. Results: Sixteen studies with over 5000 participants were included, spanning multiple countries and employing targeted or untargeted lipidomic methods. Maternal plasma, serum, placenta, and cord blood were commonly analyzed. Lipidomic alterations were consistently observed in relation to preeclampsia, GDM, FGR, and congenital anomalies. Key lipid classes included phosphatidylcholines, phosphatidylethanolamines, triglycerides, ceramides, cholesteryl esters, and diacylglycerols. These lipids mapped to metabolic pathways involving insulin resistance, inflammation, and endothelial dysfunction. Some profiles were detectable in early pregnancy, indicating potential for early risk prediction. Conclusions: Lipidomic profile analysis can reveal consistent metabolic disruptions associated with certain perinatal outcomes (such as preeclampsia, gestational diabetes, preterm birth, fetal intrauterine growth restriction, postpartum cardiometabolic risk and congenital anomalies). Lipidomic profiling reveals consistent metabolic disruptions across pregnancy complications. Lipid signatures hold promise as early biomarkers for obstetric risk stratification and may inform postpartum metabolic surveillance. Standardized approaches and mechanistic validation are needed to support clinical translation.

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