Preeclampsia (PE), the development of new-onset hypertension and proteinuria after 20 weeks gestation, is a severe pregnancy-specific disorder mediated by the placenta that affects 5% of all pregnancies. Women with prior PE have an 2-4 fold increased lifetime risk of cardiovascular disease, including ischemic heart disease and stroke. The underlying etiology of PE remains poorly understood; consequently, predictive and therapeutic options remain limited. PE has a substantial heritable component estimated at 55-60%, with both maternal and fetal contributions, estimated at 30-35% and 20%, respectively. Progress in understanding PE genetics has lagged other disorders due to: the involvement of two genomes (maternal and fetal), disease heterogeneity, the exclusion of obstetric phenotypes from many large cohort studies, and the lack of PE collections of adequate sample size for power to identify genetic risk loci. Beyond genetics, profiling of PE using other omic strategies has identified transcriptomic, proteomic, and metabolomic alterations that precede disease. However, PE cohorts with multiple omics on the same well-phenotyped individuals are lacking. To address these challenges and advance understanding of PE pathophysiology, we propose to leverage TOPMed data in the “Boston-Colombia Collaborative Adverse Pregnancy Outcome study” which capitalizes on two large, multi-ethnic pregnancy cohorts, LIFECODES (Boston) and GenPE (Colombia). LIFECODES is an ongoing longitudinal pregnancy cohort (2009–present, N >3000 pregnancies, 152 PE cases) with maternal samples from each trimester of pregnancy and delivery samples. GenPE is a Colombian study (2000 – 2012, N = 3260 cases, 4331 controls) created to identify maternal and fetal genetic risk variants. Specifically, for this proposal, we will leverage TOPMed X01 funded whole genome sequencing (WGS) on the entire LIFECODES and GenPE cohorts, as well as in-depth multi-omic profiling (metabolic, circulating microparticle proteomic and transcriptomic) on all antepartum plasma samples in matched PE case-control samples within LIFECODES, expected to be available before the grant start date. We propose three specific aims. First, we will perform gene discovery for preeclampsia using common variant, rare variant, gene based and maternal-fetal interaction analyses. Second, we will leverage longitudinal in-depth multi-omic profiling on all antepartum plasma samples in matched PE case- control samples to identify molecular subtypes of PE and link these to known and novel genetic variants. Third, we will test if polygenic risk scores for PE, supplemented by longitudinal molecular and clinical phenotypes, predict maternal morbidity at delivery and future cardiovascular disease. Taken together, analysis of this multi- omics project of PE in TOPMed, together with replication in independent cohorts, will yield novel insights into the etiology of preeclampsia. As adverse pregnancy outcomes dramatically increase the risk of ...