ArticleBMC pregnancy and childbirth2026
First-trimester plasma targeted metabolomics for eicosanoids reveals predictive potential and preventive targets for severe preeclampsia: a nested case-control study.
Article in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundEicosanoids are a diverse family of oxygenated derivatives of 20-carbon polyunsaturated fatty acids that play crucial roles in maintaining cardiovascular homeostasis. The metabolic profiles of eicosanoids preceding the onset of severe preeclampsia remain incompletely understood. This study aimed to use a targeted metabolomic approach to identify eicosanoid metabolites in first-trimester blood samples and assess their potential to predict severe preeclampsia.
methodsWithin a prospective cohort of 5,809 pregnant women, a nested case-control study analyzed 45 participants who later developed severe preeclampsia and 41 controls with uncomplicated pregnancies. Targeted metabolomic analysis was performed using Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS). Metabolomic data were examined, and predictive performance of these metabolites was evaluated using receiver operating characteristic curves.
resultsAmong 40 eicosanoids metabolites quantified, 10 metabolites differed statistically between the severe preeclampsia and control groups. Specifically, metabolites in the cyclooxygenase (COX) pathway, such as thromboxane B2 (TXB2), and the 12/15-lipoxygenase (LOX) pathway, such as 14-hydroxy-docosahexaenoic acid (14-HDoHE), were significantly upregulated in the severe preeclampsia group. Conversely, metabolites in the cytochrome P450 (CYP450) pathway, notably 19,20-epoxy-docosapentaenoic acid (19,20-EDP), were significantly downregulated. The 14-HDoHE/19,20-EDP ratio was identified as the most significant predictive marker. Integrating this ratio into the Fetal Medicine Foundation (FMF) screening algorithms significantly improved the area under the curve (AUC) from 0.77 to 0.87 (ΔAUC = 0.10, 95% confidence interval [CI]: 0.03-0.18, P = 0.008). This combined model demonstrated a sensitivity of 0.73 (95% CI: 0.60-0.86) and a specificity of 0.85 (95% CI: 0.75-0.96).
conclusionsOur findings revealed novel prediction models for severe preeclampsia based on first-trimester eicosanoid metabolomics, and provide mechanistic evidence supporting early aspirin use for COX pathway inhibition and suggest that rebalancing the 12/15-LOX and CYP450 pathways may be a potential strategy for preventing severe preeclampsia.
trial registrationChinese Clinical Trial Registry Identifier ChiCTR-EOC-15007644, registered on 03 December 2015.
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