Efficient Plasma and Placenta Metabolic Fingerprints for Preeclampsia Diagnosis: A Multicenter Study

Preeclampsia (PE) is a leading cause of maternal and perinatal mortality. There remains a clinical need for accurate and accessible diagnostic approaches to facilitate timely identification of PE. Herein, the nanoparticle-enhanced laser desorption/ionization mass spectrometry is applied to obtain plasma (n = 236) and placenta (n = 70) metabolic fingerprints from a multicenter dataset (109 PE patients and 127 non-PE participants, 4 centers). Diagnostic models are constructed with an efficient diagnostic area under the curve (AUC) of 0.941 with external validation. Subsequently, 19 PE-associated metabolites are annotated, demonstrating good diagnostic performance with an AUC of 0.871. Moreover, diagnostic scores of severe PE patients are significantly higher than those of PE patients, exhibiting our model's capacity to differentiate disease severity. Related metabolic pathways are revealed to inform potential therapeutic strategies for PE and biological validation on trophoblast cells demonstrates that key biomarkers, including L-alanine, taurine, hypoxanthine, and orotic acid, can significantly enhance migration capabilities (p < 0.01). This work highlights the potential of metabolic analysis for PE detection, paving the way for improved clinical decision-making in obstetrics.