Corresponding authorsHighlights Women with preeclampsia have increased risk of cardiovascular disease later in life but the mechanism is poorly understood. "In silico" analyses of publically available datasets provided overlapping biomarkers and pathogenic pathways between preeclampsia, hypertension and heart failure with preserved ejection fraction (HFpEF). These data could be utilised in the future studies that may lead to the development of better risk stratification strategies or preventative treatments for women post preeclampsia.
AbstractObjectives: Preeclampsia is a cardiovascular pregnancy complication which occurs in 5-10% of pregnancies that can lead to a number of pregnancy complications including maternal and foetal death. Long-term, preeclampsia is associated with up to 8-fold increased risk of cardiovascular disease (CVD) for both mothers and their offspring. The lack of mechanistic data in relation to the causes or consequences of preeclampsia has prevented the development of effective therapeutic or monitoring strategies.
Study design:This study investigates common underlying mechanisms of preeclampsia and CVD, specifically hypertension and heart failure with preserved ejection fraction (HFpEF)using "in silico" approach of publicly available datasets. Integrated techniques were designed to mine data repositories and identify relevant biomarkers associated with these three conditions.
Main outcomes measures:The knowledge base tools were employed that enabled the analysis of these biomarkers to discover potential molecular and biological links between these three conditions.Results: Our bioinformatics "in silico" analyses of the publically available datasets identified 76 common biomarkers between preeclampsia, hypertension and HFpEF. These biomarkers were representative of 29 pathways commonly enriched across the three conditions which were largely related to inflammation, metabolism, angiogenesis, remodelling, haemostasis, apoptosis, endoplasmic reticulum (ER) stress signalling and the renin-angiotensin-aldosterone (RAAS) system.
Conclusions:This bioinformatics approach which uses the wealth of scientific data available in public repositories can be helpful to gain a deeper understanding of the overlapping pathogenic mechanisms of associated diseases, which could be explored as biomarkers or targets to prevent long-term cardiovascular complications such as hypertension and HFpEF following preeclampsia.
Abstract word count: 244 wordsMain text word count: 2580 words Total word count: 4653 words