Polygenic Risk Scores for Preeclampsia Prediction Beyond Gold‐Standard Clinical Models in Multiethnic Populations

Background Preeclampsia is a major cause of maternal and fetal mortality and morbidity. Early risk stratification enables timely preventative therapy in high‐risk women. Polygenic risk scores (PGS) improve prediction in complex diseases, but their added value for preeclampsia remains unclear, particularly in comparison to gold‐standard first‐trimester prediction models and across non‐European ancestries. Methods We evaluated the performance of both a preeclampsia and systolic blood pressure PGS in 2 prospective pregnancy cohorts with detailed phenotyping: the Fetal Medicine Foundation study (n=5207; 2127 cases) and the Pregnancy Outcome Prediction study (n=3659; 228 cases). Risk models included (1) clinical factors; (2) clinical factors plus PGS; (3) advanced model including first‐trimester mean arterial pressure, PAPP‐A (pregnancy‐associated plasma protein‐A), and uterine artery pulsatility index; and (4) advanced model plus PGS. Discriminative performance, measured by the area under the receiver operating characteristic curve, was assessed overall and by ancestry. Results The preeclampsia PGS was independently associated with preeclampsia (odds ratio per SD, 1.24 95% CI, 1.17–1.31; P <0.001). It modestly improved prediction over clinical models (area under the receiver operating characteristic curve 0.746 versus 0.750; P =0.017) but not over the advanced model (area under the receiver operating characteristic curve 0.817 versus 0.818; P =0.326). The systolic blood pressure PGS showed stronger performance, improving prediction over both models in women of European ancestry. No improvement was observed with either score in women of African ancestry. Conclusions PGSs for preeclampsia and SBP provide modest added predictive value beyond clinical risk factors in European ancestry women. Limited utility in African ancestry women reflects underrepresentation in the genome‐wide association studies used to develop current scores. As cohort sizes grow and models are refined, PGSs may become important tools for equitable risk stratification in maternal health.