Mechanisms by which statins protect endothelial cells from radiation-induced injury in the carotid artery

BackgroundThe incidental use of statins during radiation therapy has been associated with a reduced long-term risk of developing atherosclerotic cardiovascular disease. However, the mechanisms by which statins protect the vasculature from irradiation injury remain poorly understood.ObjectivesIdentify the mechanisms by which the hydrophilic and lipophilic statins pravastatin and atorvastatin preserve endothelial function after irradiation.MethodsCultured human coronary and umbilical vein endothelial cells irradiated with 4 Gy and mice subjected to 12 Gy head-and-neck irradiation were pretreated with statins and tested for endothelial dysfunction, nitric oxide production, oxidative stress, and various mitochondrial phenotypes at 24 and 240 h after irradiation.ResultsBoth pravastatin (hydrophilic) and atorvastatin (lipophilic) were sufficient to prevent the loss of endothelium-dependent relaxation of arteries after head-and-neck irradiation, preserve the production of nitric oxide by endothelial cells, and suppress the cytosolic reactive oxidative stress associated with irradiation. However, only pravastatin inhibited irradiation-induced production of mitochondrial superoxide; damage to the mitochondrial DNA; loss of electron transport chain activity; and expression of inflammatory markers.ConclusionsOur findings reveal some mechanistic underpinnings of the vasoprotective effects of statins after irradiation. Whereas both pravastatin and atorvastatin can shield from endothelial dysfunction after irradiation, pravastatin additionally suppresses mitochondrial injury and inflammatory responses involving mitochondria. Clinical follow-up studies will be necessary to determine whether hydrophilic statins are more effective than their lipophilic counterparts in reducing the risk of cardiovascular disease in patients undergoing radiation therapy

Preclinical Models of Cancer Therapy-Associated Cardiovascular Toxicity:A Scientific Statement From the American Heart Association

Although cardiovascular toxicity from traditional chemotherapies has been well recognized for decades, the recent explosion of effective novel targeted cancer therapies with cardiovascular sequelae has driven the emergence of cardio-oncology as a new clinical and research field. Cardiovascular toxicity associated with cancer therapy can manifest as a broad range of potentially life-threatening complications, including heart failure, arrhythmia, myocarditis, and vascular events. Beyond toxicology, the intersection of cancer and heart disease has blossomed to include discovery of genetic and environmental risk factors that predispose to both. There is a pressing need to understand the underlying molecular mechanisms of cardiovascular toxicity to improve outcomes in patients with cancer. Preclinical cardiovascular models, ranging from cellular assays to large animals, serve as the foundation for mechanistic studies, with the ultimate goal of identifying biologically sound biomarkers and cardioprotective therapies that allow the optimal use of cancer treatments while minimizing toxicities. Given that novel cancer therapies target specific pathways integral to normal cardiovascular homeostasis, a better mechanistic understanding of toxicity may provide insights into fundamental pathways that lead to cardiovascular disease when dysregulated. The goal of this scientific statement is to summarize the strengths and weaknesses of preclinical models of cancer therapy-associated cardiovascular toxicity, to highlight overlapping mechanisms driving cancer and cardiovascular disease, and to discuss opportunities to leverage cardio-oncology models to address important mechanistic questions relevant to all patients with cardiovascular disease, including those with and without cancer.</p

Integrated genetic and epigenetic prediction of coronary heart disease in the Framingham Heart Study

<div><p>An improved method for detecting coronary heart disease (CHD) could have substantial clinical impact. Building on the idea that systemic effects of CHD risk factors are a conglomeration of genetic and environmental factors, we use machine learning techniques and integrate genetic, epigenetic and phenotype data from the Framingham Heart Study to build and test a Random Forest classification model for symptomatic CHD. Our classifier was trained on n = 1,545 individuals and consisted of four DNA methylation sites, two SNPs, age and gender. The methylation sites and SNPs were selected during the training phase. The final trained model was then tested on n = 142 individuals. The test data comprised of individuals removed based on relatedness to those in the training dataset. This integrated classifier was capable of classifying symptomatic CHD status of those in the test set with an accuracy, sensitivity and specificity of 78%, 0.75 and 0.80, respectively. In contrast, a model using only conventional CHD risk factors as predictors had an accuracy and sensitivity of only 65% and 0.42, respectively, but with a specificity of 0.89 in the test set. Regression analyses of the methylation signatures illustrate our ability to map these signatures to known risk factors in CHD pathogenesis. These results demonstrate the capability of an integrated approach to effectively model symptomatic CHD status. These results also suggest that future studies of biomaterial collected from longitudinally informative cohorts that are specifically characterized for cardiac disease at follow-up could lead to the introduction of sensitive, readily employable integrated genetic-epigenetic algorithms for predicting onset of future symptomatic CHD.</p></div

Regulation of Smooth Muscle Cell Proliferation by Mitochondrial Ca2+ in Type 2 Diabetes

Type 2 diabetes (T2D) is associated with increased risk of atherosclerotic vascular disease due to excessive vascular smooth muscle cell (VSMC) proliferation. Here, we investigated the role of mitochondrial dysfunction and Ca2+ levels in VSMC proliferation in T2D. VSMCs were isolated from normoglycemic and T2D-like mice induced by diet. The effects of mitochondrial Ca2+ uptake were studied using mice with selectively inhibited mitochondrial Ca2+/calmodulin-dependent kinase II (mtCaMKII) in VSMCs. Mitochondrial transition pore (mPTP) was blocked using ER-000444793. VSMCs from T2D compared to normoglycemic mice exhibited increased proliferation and baseline cytosolic Ca2+ levels ([Ca2+]cyto). T2D cells displayed lower endoplasmic reticulum Ca2+ levels, reduced mitochondrial Ca2+ entry, and increased Ca2+ leakage through the mPTP. Mitochondrial and cytosolic Ca2+ transients were diminished in T2D cells upon platelet-derived growth factor (PDGF) administration. Inhibiting mitochondrial Ca2+ uptake or the mPTP reduced VSMC proliferation in T2D, but had contrasting effects on [Ca2+]cyto. In T2D VSMCs, enhanced activation of Erk1/2 and its upstream regulators was observed, driven by elevated [Ca2+]cyto. Inhibiting mtCaMKII worsened the Ca2+ imbalance by blocking mitochondrial Ca2+ entry, leading to further increases in [Ca2+]cyto and Erk1/2 hyperactivation. Under these conditions, PDGF had no effect on VSMC proliferation. Inhibiting Ca2+-dependent signaling in the cytosol reduced excessive Erk1/2 activation and VSMC proliferation. Our findings suggest that altered Ca2+ handling drives enhanced VSMC proliferation in T2D, with mitochondrial dysfunction contributing to this process

Integrated genetic-epigenetic model ROC curve.

<p>The Receiver Operating Characteristic curves of the integrated genetic-epigenetic model with the largest average 10-fold cross-validation area under the curve value.</p

DNA methylation and CHD status.

<p>Top 30 significant methylation sites associated with symptomatic CHD after Bonferroni correction for multiple comparisons using training set data.</p

Summary of variables.

<p>The demographics and CHD risk factors of the 1,545 and 142 individuals included in the training and testing sets, respectively.</p

Filtering and modeling.

<p>Flowchart summarizing steps performed for Random Forest model training and testing.</p

Calmodulin kinase II is required for angiotensin II-mediated vascular smooth muscle hypertrophy

Despite our understanding that medial smooth muscle hypertrophy is a central feature of vascular remodeling, the molecular pathways underlying this pathology are still not well understood. Work over the past decade has illustrated a potential role for the multifunctional calmodulin-dependent kinase CaMKII in smooth muscle cell contraction, growth, and migration. Here we demonstrate that CaMKII is enriched in vascular smooth muscle (VSM) and that CaMKII inhibition blocks ANG II-dependent VSM cell hypertrophy in vitro and in vivo. Specifically, systemic CaMKII inhibition with KN-93 prevented ANG II-mediated hypertension and medial hypertrophy in vivo. Adenoviral transduction with the CaMKII peptide inhibitor CaMKIIN abrogated ANG II-induced VSM hypertrophy in vitro, which was augmented by overexpression of CaMKII-δ2. Finally, we identify the downstream signaling components critical for ANG II- and CaMKII-mediated VSM hypertrophy. Specifically, we demonstrate that CaMKII induces VSM hypertrophy by regulating histone deacetylase 4 (HDAC4) activity, thereby stimulating activity of the hypertrophic transcription factor MEF2. MEF2 transcription is activated by ANG II in vivo and abrogated by the CaMKII inhibitor KN-93. Together, our studies identify a complete pathway for ANG II-triggered arterial VSM hypertrophy and identify new potential therapeutic targets for chronic human hypertension

Conventional risk factors model ROC curve.

<p>The Receiver Operating Characteristic curves of the conventional risk factors model with the largest average 10-fold cross-validation area under the curve value.</p