Extracellular Vesicles From Epicardial Fat Facilitate Atrial Fibrillation.

BACKGROUND: The role of epicardial fat (eFat)-derived extracellular vesicles (EVs) in the pathogenesis of atrial fibrillation (AF) has never been studied. We tested the hypothesis that eFat-EVs transmit proinflammatory, profibrotic, and proarrhythmic molecules that induce atrial myopathy and fibrillation. METHODS: We collected eFat specimens from patients with (n=32) and without AF (n=30) during elective heart surgery. eFat samples were grown as organ cultures, and the culture medium was collected every 2 days. We then isolated and purified eFat-EVs from the culture medium, and analyzed the EV number, size, morphology, specific markers, encapsulated cytokines, proteome, and microRNAs. Next, we evaluated the biological effects of unpurified and purified EVs on atrial mesenchymal stromal cells and endothelial cells in vitro. To establish a causal association between eFat-EVs and vulnerability to AF, we modeled AF in vitro using induced pluripotent stem cell-derived cardiomyocytes. RESULTS: Microscopic examination revealed excessive inflammation, fibrosis, and apoptosis in fresh and cultured eFat tissues. Cultured explants from patients with AF secreted more EVs and harbored greater amounts of proinflammatory and profibrotic cytokines, and profibrotic microRNA, as well, than those without AF. The proteomic analysis confirmed the distinctive profile of purified eFat-EVs from patients with AF. In vitro, purified and unpurified eFat-EVs from patients with AF had a greater effect on proliferation and migration of human mesenchymal stromal cells and endothelial cells, compared with eFat-EVs from patients without AF. Last, whereas eFat-EVs from patients with and without AF shortened the action potential duration of induced pluripotent stem cell-derived cardiomyocytes, only eFat-EVs from patients with AF induced sustained reentry (rotor) in induced pluripotent stem cell-derived cardiomyocytes. CONCLUSIONS: We show, for the first time, a distinctive proinflammatory, profibrotic, and proarrhythmic signature of eFat-EVs from patients with AF. Our findings uncover another pathway by which eFat promotes the development of atrial myopathy and fibrillation.

Automated thermal imaging for the detection of fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) comprises a spectrum of progressive liver pathologies, ranging from simple steatosis to non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis. A liver biopsy is currently required to stratify high-risk patients, and predicting the degree of liver inflammation and fibrosis using non-invasive tests remains challenging. Here, we sought to develop a novel, cost-effective screening tool for NAFLD based on thermal imaging. We used a commercially available and non-invasive thermal camera and developed a new image processing algorithm to automatically predict disease status in a small animal model of fatty liver disease. To induce liver steatosis and inflammation, we fed C57/black female mice (8 weeks old) a methionine-choline deficient diet (MCD diet) for 6 weeks. We evaluated structural and functional liver changes by serial ultrasound studies, histopathological analysis, blood tests for liver enzymes and lipids, and measured liver inflammatory cell infiltration by flow cytometry. We developed an image processing algorithm that measures relative spatial thermal variation across the skin covering the liver. Thermal parameters including temperature variance, homogeneity levels and other textural features were fed as input to a t-SNE dimensionality reduction algorithm followed by k-means clustering. During weeks 3,4, and 5 of the experiment, our algorithm demonstrated a 100% detection rate and classified all mice correctly according to their disease status. Direct thermal imaging of the liver confirmed the presence of changes in surface thermography in diseased livers. We conclude that non-invasive thermal imaging combined with advanced image processing and machine learning-based analysis successfully correlates surface thermography with liver steatosis and inflammation in mice. Future development of this screening tool may improve our ability to study, diagnose and treat liver disease.