Abstract 11949: Novel First-Trimester Serum Biomarkers for Early Prediction of Preeclampsia
Yan Li, Hong-Jin Zhao, Daimin Wei, Zi-Jiang Chen- Physiology (medical)
- Cardiology and Cardiovascular Medicine
Background: Preeclampsia (PE) is a leading cause of maternal and perinatal mortality and morbidity worldwide, but effective early prediction remains a challenge due to the lack of reliable biomarkers.
Research questions: Could potential imbalances in cytokines and autoimmune antibodies be detectable in the first trimester of pregnancy in women who later develop PE?
Goals: Our study aims to discover novel biomarkers within the first trimester and construct an efficient predictive model to enhance early PE screening strategies.
Methods: Based on the extensive human biobank of our large-scale assisted reproductive cohort platform, we measured the first-trimester serum levels of 48 cytokines, total immunoglobulins (Igs), anti-phosphatidylserine (aPS) antibodies, and several previously identified PE biomarkers—including placental growth factor (PlGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and activin A—in 34 women diagnosed with PE and 34 matched normotensive controls.
Results: Our analysis revealed that the PE group exhibited significantly elevated first-trimester serum levels of hepatocyte growth factor (HGF), interleukin (IL)-2Rα, IL-9, RANTES, tumor necrosis factor-β (TNF-β), total IgM, and total IgG, and aPS IgG optical density (OD) value, in addition to decreased first-trimester serum levels of PlGF and total IgA and aPS-IgG immune complexes (IC) OD value compared to the control group. The combination of the top five first-trimester serum biomarkers (total IgM, total IgG, PlGF, aPS IgG, and total IgA) achieved superior predictive value [area under the curve (AUC) and 95% confidence interval (CI): 0.983 (0.952-1.000)] for PE development compared to PlGF and PlGF/sFlt-1 independently [AUC and 95% CI: 0.825 (0.726-0.924) and 0.670 (0.539-0.800), respectively].
Conclusion: We identified novel first-trimester serum biomarkers and developed an effective prediction model integrating immune-related factors and PlGF for early PE detection, which could facilitate the development of early diagnostic strategies and provide immunological insight into the further mechanistic exploration of PE.