Association Between Hemostatic Profiles and Hypertensive Disorders of Pregnancy: A Multi-Omics Mendelian...

Hypertensive disorders of pregnancy (HDPs) are important contributors to maternal mortality worldwide. Activation of the coagulation cascade is a hallmark of preeclampsia, but its causal role remains unclear. This study aimed to investigate the potential causal relationship between hemostatic profiles and the risk of HDPs.

To investigate the potential causal associations between hemostatic profiles and the risk of HDPs, two-sample Mendelian randomization (MR) analysis was conducted utilizing genome-wide association studies summary statistics. Subsequently, we performed proteome-wide MR analysis to further assess the causal relationship of circulating hemostatic factors on the risk of HDPs. In addition, heterogeneity test, horizontal pleiotropy test, Steiger filtering, Bonferroni correction, and Bayesian colocalization were carried out to evaluate the robustness of the findings.

Our two-sample MR analysis identified nominally significant associations between genetically predicted higher vWF (OR 1.27, 95% CI 1.06-1.51), FVIII (OR 2.21, 95% CI 1.05-4.66), and lower Protein C (OR: 0.91, 95% CI: 0.83-0.99) with a higher risk of preeclampsia. The proteome-wide MR analysis further implicated nominally significant associations for circulating levels of FII, FV, and vWF with preeclampsia risk. Sensitivity analyses showed no evidence of widespread horizontal pleiotropy or heterogeneity, and Steiger filtering confirmed the causal direction. However, these associations did not reach statistical significance after Bonferroni correction and Bayesian colocalization analysis indicated low posterior probabilities for a shared causal variant.

Our findings provide suggestive genetic evidence implicating several hemostatic factors, particularly vWF, in the pathophysiology of preeclampsia. These results suggest the potential involvement of the hemostatic system in the development of HDPs and warrant further investigation to validate these exploratory findings, given the lack of robustness after multiple testing correction.