Risk of pre-eclampsia in patients with a maternal genetic predisposition to common medical conditions: a case-control study

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Preeclampsia Prediction Using Machine Learning and Polygenic Risk Scores From Clinical and Genetic Risk Factors in Early and Late Pregnancies

BACKGROUND

Preeclampsia, a pregnancy-specific condition associated with new-onset hypertension after 20-weeks gestation, is a leading cause of maternal and neonatal morbidity and mortality. Predictive tools to understand which individuals are most at risk are needed.

METHODS

We identified a cohort of N=1125 pregnant individuals who delivered between May 2015 and May 2022 at Mass General Brigham Hospitals with available electronic health record data and linked genetic data. Using clinical electronic health record data and systolic blood pressure polygenic risk scores derived from a large genome-wide association study, we developed machine learning (XGBoost) and logistic regression models to predict preeclampsia risk.

RESULTS

Pregnant individuals with a systolic blood pressure polygenic risk score in the top quartile had higher blood pressures throughout pregnancy compared with patients within the lowest quartile systolic blood pressure polygenic risk score. In the first trimester, the most predictive model was XGBoost, with an area under the curve of 0.74. In late pregnancy, with data obtained up to the delivery admission, the best-performing model was XGBoost using clinical variables, which achieved an area under the curve of 0.91. Adding the systolic blood pressure polygenic risk score to the models did not improve the performance significantly based on De Long test comparing the area under the curve of models with and without the polygenic score.

CONCLUSIONS

Integrating clinical factors into predictive models can inform personalized preeclampsia risk and achieve higher predictive power than the current practice. In the future, personalized tools can be implemented to identify high-risk patients for preventative therapies and timely intervention to improve adverse maternal and neonatal outcomes.

Genetic contributions to risk of adverse pregnancy outcomes

Purpose of Review

Adverse pregnancy outcomes (APOs), including hypertensive disorders of pregnancy (HDP), low birthweight (LBW), and preterm birth (PTB), along with peripartum cardiomyopathy (PPCM) are associated with short- and long-term maternal and fetal cardiovascular risks. This review focuses on the genetic contributions to the risk of APOs and PPCM.

Recent Findings

The expansion of genome-wide association studies (GWAS) has led to better understanding of the biologic mechanisms underpinning APO, PPCM, and the predisposition to cardiovascular disease across the life course. Genetic loci known to be involved with the risk of hypertension (FTO, ZNF831) have been associated with the development of overall HDP and preeclampsia. Additionally, four loci significantly associated with type 2 diabetes have been associated with GDM (CDKAL1, MTNR1B, TCF7L2, CDK2NA-CDKN2B). Variants in loci known to affect genes coding for proteins involved in immune cell function and placental health (EBF1, EEFSEC, AGTR2, 2q13) have been implicated in the development of PTB and future cardiovascular risks for both the mother and the offspring. Genetic similarities in rare variants between PPCM and dilated cardiomyopathy have been described suggesting shared pathophysiologic origins as well as predisposition for future risk of heart failure, highlighting the need for the development PPCM genetic counseling guidelines.

Summary

Genetics may inform mechanisms, risk, and counseling for individuals after an APO or PPCM. Through recent advances in genetic techniques and analytic approaches, new insights into the underlying biologic mechanisms and genetic variants leading to these risks have been discovered.

Polygenic prediction of preeclampsia and gestational hypertension

Preeclampsia and gestational hypertension are common pregnancy complications associated with adverse maternal and child outcomes. Current tools for prediction, prevention and treatment are limited. Here we tested the association of maternal DNA sequence variants with preeclampsia in 20,064 cases and 703,117 control individuals and with gestational hypertension in 11,027 cases and 412,788 control individuals across discovery and follow-up cohorts using multi-ancestry meta-analysis. Altogether, we identified 18 independent loci associated with preeclampsia/eclampsia and/or gestational hypertension, 12 of which are new (for example, MTHFR-CLCN6, WNT3A, NPR3, PGR and RGL3), including two loci (PLCE1 and FURIN) identified in the multitrait analysis. Identified loci highlight the role of natriuretic peptide signaling, angiogenesis, renal glomerular function, trophoblast development and immune dysregulation. We derived genome-wide polygenic risk scores that predicted preeclampsia/eclampsia and gestational hypertension in external cohorts, independent of clinical risk factors, and reclassified eligibility for low-dose aspirin to prevent preeclampsia. Collectively, these findings provide mechanistic insights into the hypertensive disorders of pregnancy and have the potential to advance pregnancy risk stratification.

Association between preeclampsia in daughters and risk of cardiovascular disease in parents

Preeclampsia and cardiovascular disease (CVD) might share heritable underlying mechanisms. We investigated whether preeclampsia in daughters is associated with CVD in parents. In a register-based cohort study, we used Cox regression to compare rates of CVD (ischemic heart disease, ischemic stroke, myocardial infarction) in parents with ≥ 1 daughters who had preeclampsia and parents whose daughters did not have preeclampsia in Denmark, 1978-2018. Our cohort included 1,299,310 parents, of whom 87,251 had ≥ 1 daughters with preeclampsia and 272,936 developed CVD during 20,252,351 years of follow-up (incidence rate 135/10,000 person-years). Parents with one daughter who had preeclampsia were 1.19 times as likely as parents of daughters without preeclampsia to develop CVD at age < 55 years (hazard ratio [HR] 1.19, 95% confidence interval [CI] 1.13-1.25). Having ≥ 2 daughters who had preeclampsia yielded an HR of 1.88 (95% CI 1.39-2.53). The corresponding HRs for CVD at ≥ 55 years of age were 1.13 (95% CI 1.12-1.15) and 1.27 (95% CI 1.16-1.38). Patterns of association were similar for all CVD subtypes. Effect magnitudes did not differ for mothers and fathers (p = 0.52). Analyses by timing of preeclampsia onset in daughters suggested a tendency toward stronger associations with earlier preeclampsia onset, particularly in parents < 55 years. Preeclampsia in daughters was associated with increased risks of CVD in parents. Increasing strength of association with increasing number of affected daughters, equally strong associations for mothers and fathers, and stronger associations for CVD occurring before age 55 years suggest that preeclampsia and CVD share common heritable mechanisms.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Prediction of Preeclampsia from Clinical and Genetic Risk Factors in Early and Late Pregnancy Using Machine Learning and Polygenic Risk Scores

Background

Preeclampsia, a pregnancy-specific condition associated with new-onset hypertension after 20 weeks gestation, is a leading cause of maternal and neonatal morbidity and mortality. Predictive tools to understand which individuals are most at risk are needed.

Methods

We identified a cohort of N=1,125 pregnant individuals who delivered between 05/2015-05/2022 at Mass General Brigham hospitals with available electronic health record (EHR) data and linked genetic data. Using clinical EHR data and systolic blood pressure polygenic risk scores (SBP PRS) derived from a large genome-wide association study, we developed machine learning (xgboost) and linear regression models to predict preeclampsia risk.

Results

Pregnant individuals with an SBP PRS in the top quartile had higher blood pressures throughout pregnancy compared to patients within the lowest quartile SBP PRS. In the first trimester, the most predictive model was xgboost, with an area under the curve (AUC) of 0.73. Adding the SBP PRS to the models improved the performance only of the linear regression model from AUC 0.70 to 0.71; the predictive power of other models remained unchanged. In late pregnancy, with data obtained up to the delivery admission, the best performing model was xgboost using clinical variables, which achieved an AUC of 0.91.

Conclusions

Integrating clinical and genetic factors into predictive models can inform personalized preeclampsia risk and achieve higher predictive power than the current practice. In the future, personalized tools can be implemented in clinical practice to identify high-risk patients for preventative therapies and timely intervention to improve adverse maternal and neonatal outcomes.

Effects of Pre-Pregnancy Overweight/Obesity on the Pattern of Association of Hypertension Susceptibility Genes with Preeclampsia

The aim of this study was to explore the effects of pre-pregnancy overweight/obesity on the pattern of association of hypertension susceptibility genes with preeclampsia (PE). Ten single-nucleotide polymorphisms (SNPs) of the 10 genome-wide association studies (GWAS)-significant hypertension/blood pressure (BP) candidate genes were genotyped in 950 pregnant women divided into two cohorts according to their pre-pregnancy body mass index (preBMI): preBMI ≥ 25 (162 with PE and 159 control) and preBMI < 25 (290 with PE and 339 control). The PLINK software package was utilized to study the association (analyzed four genetic models using logistic regression). The functionality of PE-correlated loci was analyzed by performing an in silico database analysis. Two SNP hypertension/BP genes, rs805303 BAG6 (OR: 0.36−0.66) and rs167479 RGL3 (OR: 1.86), in subjects with preBMI ≥ 25 were associated with PE. No association between the studied SNPs and PE in the preBMI < 25 group was determined. Further analysis showed that two PE-associated SNPs are functional (have weighty eQTL, sQTL, regulatory, and missense values) and could be potentially implicated in PE development. In conclusion, this study was the first to discover the modifying influence of overweight/obesity on the pattern of association of GWAS-significant hypertension/BP susceptibility genes with PE: these genes are linked with PE in preBMI ≥ 25 pregnant women and are not PE-involved in the preBMI < 25 group.

Polymorphisms of hypertension susceptibility genes as a risk factors of preeclampsia in the Caucasian population of central Russia

INTRODUCTION

The study was designed to assess the effects of hypertension (HT) susceptibility genes polymorphisms in the development of preeclampsia (PE) in Caucasians from Central Russia.

METHODS

PE patients (n = 452) and women control group (n = 498) were genotyped for 10 polymorphisms of HT/blood pressure (BP) susceptibility genes (according to the previously published GWAS in Caucasian populations) including AC026703.1 (rs1173771), HFE (rs1799945), BAG6 (rs805303), PLCE1 (rs932764), OBFC1 (rs4387287), ARHGAP42 (rs633185), CERS5 (rs7302981), ATP2B1 (rs2681472), TBX2 (rs8068318) and RGL3 (rs167479). A logistic regression method was applied to search for associations between SNPs and PE. The relationship between SNP-SNP interactions and PE risk was analyzed by performing MB-MDR.

RESULTS

The rs1799945 gene in HFE significantly independently increased the risk of developing PE (OR = 2.24) and rs805303 in BAG6 was associated with a reduced risk in the occurrence of PE (OR = 0.55-0.78). Among the 10 SNPs examined, nine SNPs were associated with PEs within the 10 most significant SNP-SNP interaction models. Loci rs7302981 CERS5, rs805303 BAG6 and rs932764 PLCE1 contributed to the largest number of epistatic models (50% or more).

DISCUSSION

The present study is the first to report an association between polymorphisms of HT/BP susceptibility genes important for GWAS and the risk of PE in Caucasians from Central Russia. Our pathway-based functional annotation of the PE risk variants highlights the potential regulatory function (epigenetic/eQTL/sQTL/non-synonymous) that nine genetic risk markers and their 115 highly correlated variants exert on 155 genes. The study shows that these genes may function cooperatively in key signaling pathways in PE biology.

Pregnancy and Reproductive Risk Factors for Cardiovascular Disease in Women

Beyond conventional risk factors for cardiovascular disease, women face an additional burden of sex-specific risk factors. Key stages of a woman's reproductive history may influence or reveal short- and long-term cardiometabolic and cardiovascular trajectories. Early and late menarche, polycystic ovary syndrome, infertility, adverse pregnancy outcomes (eg, hypertensive disorders of pregnancy, gestational diabetes, preterm delivery, and intrauterine growth restriction), and absence of breastfeeding are all associated with increased future cardiovascular disease risk. The menopause transition additionally represents a period of accelerated cardiovascular disease risk, with timing (eg, premature menopause), mechanism, and symptoms of menopause, as well as treatment of menopause symptoms, each contributing to this risk. Differences in conventional cardiovascular disease risk factors appear to explain some, but not all, of the observed associations between reproductive history and later-life cardiovascular disease; further research is needed to elucidate hormonal effects and unique sex-specific disease mechanisms. A history of reproductive risk factors represents an opportunity for comprehensive risk factor screening, refinement of cardiovascular disease risk assessment, and implementation of primordial and primary prevention to optimize long-term cardiometabolic health in women.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

C1431T Variant of PPARγ Is Associated with Preeclampsia in Pregnant Women

Peroxisome proliferator-activated receptor γ (PPARγ) is essential for placental development, whose SNPs have shown increased susceptibility to pregnancy-related diseases, such as preeclampsia. Our aim was to investigate the association between preeclampsia and three PPARγ SNPs (Pro12Ala, C1431T, and C681G), which together with nine clinical factors were used to build a pragmatic model for preeclampsia prediction. Data were collected from 1648 women from the EDEN cohort, of which 35 women had preeclamptic pregnancies, and the remaining 1613 women had normal pregnancies. Univariate analysis comparing preeclamptic patients to the control resulted in the SNP C1431T being the only factor significantly associated with preeclampsia (p < 0.05), with a confidence interval of 95% and odds ratio ranging from 4.90 to 8.75. On the other hand, three methods of multivariate feature selection highlighted seven features that could be potential predictors of preeclampsia: maternal C1431T and C681G variants, obesity, body mass index, number of pregnancies, primiparity, cigarette use, and education. These seven features were further used as input into eight different machine-learning algorithms to create predictive models, whose performances were evaluated based on metrics of accuracy and the area under the receiver operating characteristic curve (AUC). The boost tree-based model performed the best, with respective accuracy and AUC values of 0.971 ± 0.002 and 0.991 ± 0.001 in the training set and 0.951 and 0.701 in the testing set. A flowchart based on the boost tree model was constructed to depict the procedure for preeclampsia prediction. This final decision tree showed that the C1431T variant of PPARγ is significantly associated with susceptibility to preeclampsia. We believe that this final decision tree could be applied in the clinical prediction of preeclampsia in the very early stages of pregnancy.

STOX1 deficiency is associated with renin-mediated gestational hypertension and placental defects

The pathogenesis of preeclampsia and other hypertensive disorders of pregnancy remains poorly defined despite the substantial burden of maternal and neonatal morbidity associated with these conditions. In particular, the role of genetic variants as determinants of disease susceptibility is understudied. Storkhead-box protein 1 (STOX1) was first identified as a preeclampsia risk gene through family-based genetic linkage studies in which loss-of-function variants were proposed to underlie increased preeclampsia susceptibility. We generated a genetic Stox1 loss-of-function mouse model (Stox1 KO) to evaluate whether STOX1 regulates blood pressure in pregnancy. Pregnant Stox1-KO mice developed gestational hypertension evidenced by a significant increase in blood pressure compared with WT by E17.5. While severe renal, placental, or fetal growth abnormalities were not observed, the Stox1-KO phenotype was associated with placental vascular and extracellular matrix abnormalities. Mechanistically, we found that gestational hypertension in Stox1-KO mice resulted from activation of the uteroplacental renin-angiotensin system. This mechanism was supported by showing that treatment of pregnant Stox1-KO mice with an angiotensin II receptor blocker rescued the phenotype. Our study demonstrates the utility of genetic mouse models for uncovering links between genetic variants and effector pathways implicated in the pathogenesis of hypertensive disorders of pregnancy.