Integrated systems biology approach identifies gene targets for endothelial dysfunction.

Endothelial dysfunction (ED) is critical in the development and progression of cardiovascular (CV) disorders, yet effective therapeutic targets for ED remain elusive due to limited understanding of its underlying molecular mechanisms. To address this gap, we employed a systems biology approach to identify potential targets for ED. Our study combined multi omics data integration, with siRNA screening, high content imaging and network analysis to prioritise key ED genes and identify a pro- and anti-ED network.

Missing links in preeclampsia cell model systems of endothelial dysfunction.

Preeclampsia, one of the main hypertensive disorders of pregnancy, is associated with circulating factors released by the ischemic placenta accompanied by systemic endothelial dysfunction. The etiology of preeclampsia remains poorly understood although it is associated with high maternal and fetal mortality and increased cardiovascular disease risk. Most cell model systems used for studying endothelial dysfunction have not taken into account hemodynamic physical factors such as shear-stress forces which may prevent extrapolation of cell data to in vivo settings.

Uncovering emergent phenotypes in endothelial cells by clustering of surrogates of cardiovascular risk factors.

Endothelial dysfunction (ED) is a hallmark of atherosclerosis and is influenced by well-defined risk factors, including hypoxia, dyslipidemia, inflammation, and oscillatory flow. However, the individual and combined contributions to the molecular underpinnings of ED remain elusive. We used global gene expression in human coronary artery endothelial cells to identify gene pathways and cellular processes in response to chemical hypoxia, oxidized lipids, IL-1β induced inflammation, oscillatory flow, and these combined stimuli.

Carotid intima-media thickness and metabolic syndrome in a rural population: Results from the Baependi Heart Study.

Background And Aims: Carotid intima-media thickness (cIMT) is a strong predictor of cardiovascular events and associated with metabolic syndrome (MetS). MetS is a cluster of cardiovascular risk factors, but the association structure between specific factors and disease development is not well-established in rural populations. We described the association structure between MetS factors and cIMT in a sample from rural Brazil.