First trimester serum biomarker discovery study for early onset, preterm onset and preeclampsia at term

Proteome-Based Maternal Plasma and Serum Biomarkers for Preeclampsia: A Systematic Review and Meta-Analysis

Proteomics has emerged as a transformative tool in biomedical research, enabling comprehensive characterization of protein profiles in complex biological systems. In preeclampsia (PE) research, quantitative proteomic analyses of plasma and serum have revealed critical insights into disease mechanisms and potential biomarkers. Through a systematic review of 17 studies (2009-2024), we identified 561 differentially expressed plasma/serum proteins (p < 0.05) in PE patients versus healthy controls, with 122 proteins consistently replicated across ≥2 independent studies. Stratified analysis by clinical subtype (early-vs. late-onset PE) demonstrated both concordant and divergent protein expression patterns, reflecting heterogeneity in PE pathophysiology, methodological variations (e.g., sample processing, proteomic platforms), and differences between discovery-phase and targeted validation studies. The trimester-specific biomarker panels proposed here offer a framework for future large-scale, multicenter validation. By integrating advanced proteomic technologies with standardized preanalytical and analytical protocols, these findings advance opportunities for early prediction (first-trimester biomarker signatures); mechanistic insight (complement system involvement); and personalized management (subtype-specific therapeutic targets). This work underscores the potential of proteomics to reshape PE research, from molecular discovery to clinical translation, ultimately improving outcomes for this leading cause of maternal and perinatal morbidity.

Proteomic Profiles of Maternal Plasma Extracellular Vesicles for Prediction of Preeclampsia

PROBLEM

Preeclampsia is a heterogeneous syndrome of diverse etiologies and molecular pathways leading to distinct clinical subtypes. Herein, we aimed to characterize the extracellular vesicle (EV)-associated and soluble fractions of the maternal plasma proteome in patients with preeclampsia and to assess their value for disease prediction.

METHOD OF STUDY

This case-control study included 24 women with term preeclampsia, 23 women with preterm preeclampsia, and 94 healthy pregnant controls. Blood samples were collected from cases on average 7 weeks before the diagnosis of preeclampsia and were matched to control samples. Soluble and EV fractions were separated from maternal plasma; EVs were confirmed by cryo-EM, NanoSight, and flow cytometry; and 82 proteins were analyzed with bead-based, multiplexed immunoassays. Quantile regression analysis and random forest models were implemented to evaluate protein concentration differences and their predictive accuracy. Preeclampsia subgroups defined by molecular profiles were identified by hierarchical cluster analysis. Significance was set at p < 0.05 or false discovery rate-adjusted q < 0.1.

RESULTS

In preterm preeclampsia, PlGF, PTX3, and VEGFR-1 displayed differential abundance in both soluble and EV fractions, whereas angiogenin, CD40L, endoglin, galectin-1, IL-27, CCL19, and TIMP1 were changed only in the soluble fraction (q < 0.1). The direction of changes in the EV fraction was consistent with that in the soluble fraction for nine proteins. In term preeclampsia, CCL3 had increased abundance in both fractions (q < 0.1). The combined EV and soluble fraction proteomic profiles predicted preterm and term preeclampsia with an AUC of 78% (95% CI, 66%-90%) and 68% (95% CI, 56%-80%), respectively. Three clusters of preeclampsia featuring distinct clinical characteristics and placental pathology were identified based on combined protein data.

CONCLUSIONS

Our findings reveal distinct alterations of the maternal EV-associated and soluble plasma proteome in preterm and term preeclampsia and identify molecular subgroups of patients with distinct clinical and placental histopathologic features.

Risk factors for preeclampsia in patients with chronic kidney disease primarily focused on stage 1 CKD. Are referred and registered patients alike?

Limited research exists on identifying risk factors for preeclampsia (PE) in the chronic kidney disease (CKD) population, especially across different patient sources. This study aimed to address this gap by analyzing clinical data from CKD pregnant women admitted to Peking University Third Hospital from January 2012 to December 2022. Logistic regression analysis identified independent risk factors for PE in the CKD population and assessed variations among patients from different sources. Additionally, a predictive model for PE was established using data from the registered group. The study included 524 CKD patients. Hypertension, proteinuria, fibrinogen >4 g/L, serum albumin ≤30 g/L, and uric acid >260 μmol/L were independent risk factors for PE in the overall CKD population. Subgroup analysis revealed that hypertension, serum albumin ≤30 g/L, and uric acid >260 μmol/L were independent risk factors in the referred group, while hypertension, uric acid >260 μmol/L, and fibrinogen >4 g/L were independent risk factors in the registered group. The prediction model based on registered group risk factors showed good predictive efficiency, with the area under the curve of 0.774 in the training set and 0.714 in the validation set. In conclusion, this study revealed that hypertension and elevated uric acid are independent risk factors for PE in CKD patients regardless of patient source, while serum albumin and fibrinogen levels are associated with PE risk in specific patient subgroups. Our predictive model enables clinicians to quickly identify the risk of PE in CKD patients, and early intervention treatment to improve pregnancy outcomes.

Predicting Preterm Birth Using Proteomics

The complexity of preterm birth (PTB), both spontaneous and medically indicated, and its various etiologies and associated risk factors pose a significant challenge for developing tools to accurately predict risk. This review focuses on the discovery of proteomics signatures that might be useful for predicting spontaneous PTB or preeclampsia, which often results in PTB. We describe methods for proteomics analyses, proteomics biomarker candidates that have so far been identified, obstacles for discovering biomarkers that are sufficiently accurate for clinical use, and the derivation of composite signatures including clinical parameters to increase predictive power.

Classification of preeclampsia according to molecular clusters with the goal of achieving personalized prevention

The prevention of pre-eclampsia is difficult due to the syndromic nature and multiple underlying mechanisms of this severe complication of pregnancy. The current clinical distinction between early- and late-onset disease, although clinically useful, does not reflect the true nature and complexity of the pathologic processes leading to pre-eclampsia. The current gaps in knowledge on the heterogeneous molecular pathways of this syndrome and the lack of adequate, specific diagnostic methods are major obstacles to early screening and tailored preventive strategies. The development of novel diagnostic tools for detecting the activation of the identified disease pathways would enable early, accurate screening and personalized preventive therapies. We implemented a holistic approach that includes the utilization of different proteomic profiling methods of maternal plasma samples collected from various ethnic populations and the application of systems biology analysis to plasma proteomic, maternal demographic, clinical characteristic, and placental histopathologic data. This approach enabled the identification of four molecular subclasses of pre-eclampsia in which distinct and shared disease mechanisms are activated. The current review summarizes the results and conclusions from these studies and the research and clinical implications of our findings.

Recognizing Early Warning Signs of Acute Hypertensive Crisis of the Postpartum Mother: An Important Role for Neonatal Nurses

A delay in detecting acute hypertensive crisis in postpartum mothers can exacerbate complications in the mother. Neonatal nurses are uniquely qualified to identify postpartum warning signs in mothers while they are in the NICU with their infants. Few research studies have explored the use of neonatal nurse screenings for acute hypertensive crisis in postpartum mothers. NICU nurses screening mothers for postpartum depression has yielded success in improving outcomes, and this model could be translated into screening for acute hypertensive crisis. Further education should be implemented for NICU nurses that include a review of adult blood pressure monitoring, early warning signs, and symptoms of preeclampsia that the mother should report. This article discusses the importance of the neonatal nurse's role in identifying early warning signs of maternal postpartum hypertensive crisis.

Early pregnancy biomarker discovery study for spontaneous preterm birth

(1) OBJECTIVE: discover new candidate biomarkers for spontaneous preterm birth in early pregnancy samples. When fully clinically validated, early pregnancy biomarkers for sPTB give the possibility to intervene or monitor high-risk pregnancies more intensively through, as example, pelvic exams, ultrasound or sonographic cervical length surveillance. (2) STUDY DESIGN: Early pregnancy serum samples of eight spontaneous extreme and very preterm birth cases (<32 weeks of gestational age) without any symptoms of preeclampsia and fetal growth restriction and eight uncomplicated pregnancies were analyzed by liquid chromatography mass spectrometry (LC-MS). Thirteen proteins, which were differentially expressed according to the LC-MS data, were subsequently selected for confirmation by enzyme-linked immunosorbent assay (ELISA). (3) RESULTS: Differential expression of four candidate biomarkers was confirmed by ELISA with decreased early pregnancy levels of gelsolin and fibulin-1 and increased levels of c-reactive protein and complement C5 in the preterm birth group. (4) CONCLUSIONS: The confirmed candidate biomarkers are all to some extent related to inflammatory pathways and/or the complement system. This supports the hypothesis that both play a role in extreme and very preterm birth without any symptoms of preeclampsia and fetal growth restriction. The predictive value of complement C5, c-reactive protein, fibulin-1 and gelsolin should, therefore, be validated in another cohort with early pregnancy samples.