Abstract Body: Introduction: Early prediction of preeclampsia remains a critical unmet need in obstetric care. The renin-angiotensin aldosterone system (RAAS) plays a central role in blood pressure regulation and placental development, yet its utility for the prediction of pre-eclampsia is understudied. ALDO+ (previously RAAS-Triple A) is a mass spectrometry-based platform for quantifying equilibrium concentrations of angiotensin I (Ang I), angiotensin II (Ang II), and aldosterone, enabling derivation of physiologically meaningful RAAS biomarkers.

Purpose: The purpose of this study was to evaluate whether RAAS biomarkers measured using the ALDO+ platform could distinguish patients with preeclampsia from non-pre-eclamptic pregnancies and identify those at risk for developing preeclampsia later in gestation.

Methods: We conducted a gestational age–matched case-control study of pregnant patients with and without preeclampsia (mean 28 weeks gestation; 51 cases, 49 controls). ALDO+ was used to measure Ang I, Ang II, and aldosterone. Receiver operating characteristics analyses were performed to evaluate predictive performance of individual biomarkers. A cut-off for the Ang II to Ang I ratio (ACE-R) was identified in the case-control study. This cut-off was then applied to an independent longitudinal cohort of 130 pregnant patients sampled at 28 weeks, 14 of whom subsequently developed preeclampsia.

Results: In the case-control cohort, ACE-R was significantly elevated in preeclampsia cases. A cut-off of ACE-R >2.05 predicted preeclampsia with 84% sensitivity and 61.2% specificity (AUC=0.85). When applied to the longitudinal cohort, this cut-off identified 7 of 14 individuals who later developed preeclampsia (50% sensitivity) and correctly excluded 81 of 116 who did not (70% specificity). Other RAAS markers, including individual concentrations of Ang I, Ang II, and aldosterone, showed good but lower predictive performance.

Conclusions: RAAS activity biomarkers derived using ALDO+ demonstrated potential for predicting preeclampsia in non-optimized cohorts. The ACE-R in particular showed promising sensitivity and specificity for disease identification and prediction. These results support further investigation of RAAS-based biomarkers in prospective cohorts for risk stratification in pregnancy (alone or in combination with current tools) and provide a mechanistically grounded framework for preeclampsia prediction.