Abstract 9129: Effect of Cardiovascular Risk Factors on Hypertensive Disorders of Pregnancy: A Mendelian Randomization Study

Abstract

Introduction: Cardiovascular risk factors have been associated with adverse maternal and fetal outcomes, including risk of hypertensive disorders of pregnancy such as pre-eclampsia (PE) and low fetal birth weight. However, it is difficult to establish causal relationships from retrospective evidence due to risk of confounding. We applied Mendelian randomization to explore the role of traditional cardiovascular risk factors in determining maternal and fetal outcomes of pregnancy. Methods: Summary statistics were used to perform a 2-sample Mendelian randomization study to investigate the association of genetically-predicted systolic blood pressure (SBP), body mass index (BMI), glycated haemoglobin A1C (HbA1C), low-density lipoprotein cholesterol (LDL-C), and smoking with the primary outcome of pre-eclampsia or eclampsia in 1,689 cases and 52,576 controls of Finnish ancestry, and secondary outcome of birth weight of the first child of 145,558 European women from the UK Biobank. Results: There was a significant association between PE and both genetically-predicted SBP (OR per mmHg increase: 1.05,95%CI 1.01-1.10, p=0.030) and genetically-predicted BMI (OR per kg/m 2 increase: 0.24 95%CI 1.07-1.90 p=0.017). Genetically-predicted SBP was associated with lower birth weight (OR per mmHg increase: 0.98, 95%CI 0.97-0.98 p<0.001), whereas genetically-predicted HbA1C was associated with higher birth weight (OR per mmol/mol increase: 1.31 95%CI 1.11-1.56 p=0.002). Conclusion: Our results suggest a causal association between some cardiovascular risk factors, specifically hypertension, obesity and HbA1C, with adverse maternal and fetal outcomes, such as pre-eclampsia and low fetal birth weight. No causal association was found for LDL-C and smoking.The results provide insight into the genetic and pathophysiological basis of pre-eclampsia and identify important targets for pre-pregnancy counselling and optimization to improve maternal and fetal outcomes.