ImportanceA genetic contribution to preeclampsia susceptibility has been established but is still incompletely understood.ObjectiveTo disentangle the underlying genetic architecture of preeclampsia and preeclampsia or other maternal hypertension during pregnancy with a genome-wide association study (GWAS) of hypertensive disorders of pregnancy.Design, Setting, and ParticipantsThis GWAS included meta-analyses in maternal preeclampsia and a combination phenotype encompassing maternal preeclampsia and preeclampsia or other maternal hypertensive disorders. Two overlapping phenotype groups were selected for examination, namely, preeclampsia and preeclampsia or other maternal hypertension during pregnancy. Data from the Finnish Genetics of Pre-eclampsia Consortium (FINNPEC, 1990-2011), Finnish FinnGen project (1964-2019), Estonian Biobank (1997-2019), and the previously published InterPregGen consortium GWAS were combined. Individuals with preeclampsia or other maternal hypertension during pregnancy and control individuals were selected from the cohorts based on relevant International Classification of Diseases codes. Data were analyzed from July 2020 to February 2023.ExposuresThe association of a genome-wide set of genetic variants and clinical risk factors was analyzed for the 2 phenotypes.ResultsA total of 16 743 women with prior preeclampsia and 15 200 with preeclampsia or other maternal hypertension during pregnancy were obtained from FINNPEC, FinnGen, Estonian Biobank, and the InterPregGen consortium study (respective mean [SD] ages at diagnosis: 30.3 [5.5], 28.7 [5.6], 29.7 [7.0], and 28 [not available] years). The analysis found 19 genome-wide significant associations, 13 of which were novel. Seven of the novel loci harbor genes previously associated with blood pressure traits (NPPA, NPR3, PLCE1, TNS2, FURIN, RGL3, and PREX1). In line with this, the 2 study phenotypes showed genetic correlation with blood pressure traits. In addition, novel risk loci were identified in the proximity of genes involved in the development of placenta (PGR, TRPC6, ACTN4, and PZP), remodeling of uterine spiral arteries (NPPA, NPPB, NPR3, and ACTN4), kidney function (PLCE1, TNS2, ACTN4, and TRPC6), and maintenance of proteostasis in pregnancy serum (PZP).Conclusions and RelevanceThe findings indicate that genes related to blood pressure traits are associated with preeclampsia, but many of these genes have additional pleiotropic effects on cardiometabolic, endothelial, and placental function. Furthermore, several of the associated loci have no known connection with cardiovascular disease but instead harbor genes contributing to maintenance of successful pregnancy, with dysfunctions leading to preeclampsialike symptoms.
Background - Acute coronary syndrome (ACS) is a clinically significant presentation of coronary heart disease (CHD). Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual's genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS. Methods - We explored the association between 405 clinical conditions diagnosed before baseline and 9,080 incident cases of ACS in 387,832 individuals from the UK Biobank. Results were replicated in 6,430 incident cases of ACS in 177,876 individuals from FinnGen. Results - We identified 80 conventional (e.g., stable angina pectoris (SAP), type 2 diabetes mellitus) and unconventional (e.g., diaphragmatic hernia, inguinal hernia) associations with ACS. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of SAP yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction p-value=2.87×10-8) risk for ACS in individuals with SAP (HR=1.163 [95% CI: 1.082-1.251]) compared to individuals without SAP (HR=1.531 [95% CI: 1.497-1.565]). These findings were replicated in FinnGen (interaction p-value=1.38×10-6). Conclusions - In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable CHD. PS may be more appropriate for prediction of ACS in asymptomatic individuals than symptomatic individuals with clinical suspicion for CHD.
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