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. We found 26 genes that, upon silencing, exacerbated the ED phenotypes tested, and network propagation identified a pro-ED network enriched in functions associated with inflammatory responses. Conversely, 31 genes ameliorated ED phenotypes, pointing to potential ED targets, and the respective anti-ED network was enriched in hypoxia, angiogenesis and cancer-related processes. An independent screen with 17 drugs found general agreement with the trends from our siRNA screen and further highlighted DUSP1, IL6 and CCL2 as potential candidates for targeting ED. Overall, our results demonstrate the potential of integrated system biology approaches in discovering disease-specific candidate drug targets for endothelial dysfunction.

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. We overview the role of hemodynamic forces in modulating endothelial cell function and discuss strategies to reproduce this biological characteristic in vitro to improve our understanding of endothelial dysfunction associated with preeclampsia.

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-1ß induced inflammation, oscillatory flow, and these combined stimuli. We found that clustering of the surrogate risk factors differed from the sum of the individual insults that gave rise to emergent phenotypes such as cell proliferation. We validated these observations in samples of human coronary artery atherosclerotic plaques analyzed using single-cell RNA sequencing. Our findings suggest a hierarchical interaction between surrogates of CV risk factors and the advent of emergent phenotypes in response to combined stimulation in endothelial cells that may influence ED.

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. METHODS: We studied 1937 participants from the Baependi Heart Study who underwent carotid ultrasound exam. We used ATP-III-2001 for MetS definition and linear mixed-effects models, adjusting by the family structure, to assess independent associations between the cardiovascular risk factors which define MetS and cIMT. RESULTS: The sample's mean age was 46 ± 16y, 61% female, 73% white, mean body-mass-index 26±5 kg/m2, mean cIMT 0.53 ± 0.16 mm, with 35% of the sample classified with MetS. As expected, cIMT demonstrated a linear relationship with increasing age, and cIMT higher values were observed for MetS (0.58 ± 0.16 mm) compared to non-MetS (0.49 ± 0.14 mm). Considering models for cIMT with MetS and all of its factors, we found that blood pressure, glucose and obesity were independently associated with cIMT, but not HDL or triglycerides. CONCLUSIONS: cIMT showed a linear relationship with increasing age. Blood pressure, obesity, and glucose were independently associated with cIMT, but not HDL-cholesterol or triglycerides. In a rural population, hypertension, diabetes and obesity play a more important role than lipids in determining cIMT interindividual variability.