Preeclampsia prediction with maternal and paternal polygenic risk scores: the TMM BirThree Cohort Study

Abstract

Background: Genomic information from pregnant women and their husbands may provide effective biomarkers for preeclampsia. This study investigated how parental polygenic risk scores (PRSs) for blood pressure (BP) and preeclampsia are associated with preeclampsia onset and evaluated predictive performances of PRSs with clinical predictive variables. Methods: In the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study, participants were genotyped using either Affymetrix Axiom Japonica Array v2 (further divided into two cohorts?the PRS training cohort and the internal-validation cohort?at a ratio of 1:2) or Japonica Array NEO (external-validation cohort). PRSs were calculated for systolic BP (SBP), diastolic BP (DBP), and preeclampsia. Associations between PRSs and preeclampsia, including preeclampsia superimposed on chronic hypertension, were examined using logistic regression analysis; prediction models were developed using a competing-risks approach with clinical predictive variables and PRSs. Results: In total, 19,836 participants were included. Hyperparameters for PRS calculation were optimized for 3,384 participants in the training cohort. In internal- and external-validation cohorts, 357 of 6,768 (5.3%) and 269 of 9,684 (2.8%) participants developed preeclampsia, respectively. Preeclampsia onset was significantly associated with maternal PRSs for SBP and DBP in internal- and external-validation cohorts and with paternal PRSs for SBP and DBP only in the external-validation cohort. Maternal PRSs for DBP calculated using ?LDpred2? most improved prediction models. Maternal PRSs for DBP provided additional predictive information on clinical predictive variables. Paternal PRSs for DBP improved prediction models in the internal-validation cohort. Conclusions: Parental PRS, along with clinical predictive variables, is potentially useful for predicting preeclampsia.