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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]; <0.001). It modestly improved prediction over clinical models (area under the receiver operating characteristic curve 0.746 versus 0.750; =0.017) but not over the advanced model (area under the receiver operating characteristic curve 0.817 versus 0.818; =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.