Relationship between the volume of perivascular adipose tissue and the vascular wall lesion

Aim. To study the relationship between the volume of perivascular adipose tissue (PVAT) and the vascular wall lesion.Material and methods. The study included 318 patients without cardiovascular disease (mean age, 63,5±13,7 years). Hypertension was detected in 268 (84,3%) patients. All patients underwent assessment of anthropometric characteristics, lipid profile, arterial wall stiffness with the estimation of cardio-ankle vascular index, intima-media thickness, brachial artery endothelial vasomotor function. Chest computed tomography was performed with the estimation of the volumes of PVAT and pericardial adipose tissue (PAT).Results. The volume of PVAT, on average, was 0,3 [0,2; 0,4] cm3 . The VAT volume was significantly higher in obese individuals when compared with patients with normal body weight: 0,4 [0,3; 0,5] vs 0,25 [0,2; 0,4] cm3 (p=0,0007). The VAT volume was higher in individuals with an increased CAVI level when compared with patients with normal CAVI values: 0,4 [0,3; 0,5] vs 0,3 [0,25; 0,3] (p=0,02). A significant correlation was found between the VAT volume and body mass index (r=0,27, p<0,005), waist circumference (r=0,41, p<0,005), CAVI (r=0,49, p<0,05), impaired endothelium-dependent brachial artery vasodilation (r=0,38, p<0,05). When performing multiple linear regression, a significant relationship of CAVI was found with age (β±SE, 0,51±0,15; p=0,002) and volume of PVAT (β±SE, 0,41±0,13; p=0,005).Conclusion. The results indicate the relationship of PVAT with visceral obesity and vascular wall stiffness parameters.

Multiscale Biology of Cardiovascular Risk in Psoriasis: Protocol for a Case-Control Study

Background Patients with psoriasis have increased risk of cardiovascular disease (CVD) independent of traditional risk factors. The molecular mechanisms underlying the psoriasis-CVD connection are not fully understood. Advances in high-throughput molecular profiling technologies and computational analysis techniques offer new opportunities to improve the understanding of disease connections. Objective We aim to characterize the complexity of cardiovascular risk in patients with psoriasis by integrating deep phenotypic data with systems biology techniques to perform comprehensive multiomic analyses and construct network models of the two interacting diseases. Methods The study aims to include 120 adult patients with psoriasis (60 with prior atherosclerotic CVD and 60 without CVD). Half of the patients are already receiving systemic antipsoriatic treatment. All patients complete a questionnaire, and a medical interview is conducted to collect medical history and information on, for example, socioeconomics, mental health, diet, and physical exercise. Participants are examined clinically with assessment of the Psoriasis Area and Severity Index and undergo imaging by transthoracic echocardiography, 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT), and carotid artery ultrasonography. Skin swabs are collected for analysis of microbiome metagenomics; skin biopsies and blood samples are collected for transcriptomic profiling by RNA sequencing; skin biopsies are collected for immunohistochemistry; plasma samples are collected for analyses of proteomics, lipidomics, and metabolomics; blood samples are collected for high-dimensional mass cytometry; and feces samples are collected for gut microbiome metagenomics. Bioinformatics and systems biology techniques are utilized to analyze the multiomic data and to integrate data into a network model of CVD in patients with psoriasis. Results Recruitment was completed in September 2020. Preliminary results of 18F-FDG-PET/CT data have recently been published, where vascular inflammation was reduced in the ascending aorta (P=.046) and aortic arch (P=.04) in patients treated with statins and was positively associated with inflammation in the visceral adipose tissue (P<.001), subcutaneous adipose tissue (P=.007), pericardial adipose tissue (P<.001), spleen (P=.001), and bone marrow (P<.001). Conclusions This systems biology approach with integration of multiomics and clinical data in patients with psoriasis with or without CVD is likely to provide novel insights into the biological mechanisms underlying these diseases and their interplay that can impact future treatment. International Registered Report Identifier (IRRID) DERR1-10.2196/28669

Association of Pericardiac Adipose Tissue With Coronary Artery Disease

Background and AimCoronary artery disease (CAD) poses a worldwide health threat. Compelling evidence shows that pericardial adipose tissue (PAT), a brown-like adipose adjacent to the external surface of the pericardium, is associated with CAD. However, the specific molecular mechanisms of PAT in CAD are elusive. This study aims to characterize human PAT and explore its association with CAD.MethodsWe acquired samples of PAT from 31 elective cardiac surgery patients (17 CAD patients and 14 controls). The transcriptome characteristics were assessed in 5 CAD patients and 4 controls via RNA-sequencing. Cluster profile R package, String database, Cytoscape were applied to analyze the potential pathways and PPI-network key to DEGS, whereas the hubgenes were predicted via Metascape, Cytohubba, and MCODE. We use Cibersort, ENCORI, and DGIDB to predict immunoinfiltration, mRNA-miRNA target gene network, and search potential drugs targeting key DEGs. The predictable hubgenes and infiltrating inflammatory cells were validated in 22 patients (12 CAD samples and 10 control samples) through RT-qPCR and immunohistochemistry.ResultsA total of 147 different genes (104 up-regulated genes and 43 down-regulated genes) were identified in CAD patients. These different genes were associated with immunity and inflammatory dysfunction. Cibersort analysis showed monocytes and macrophages were the most common subsets in immune cells, whereas immunohistochemical results revealed there were more macrophages and higher proportion of M1 subtype cells in PAT of CAD patients. The PPI network and module analysis uncovered several crucial genes, defined as candidate genes, including Jun, ATF3, CXCR4, FOSB, CCl4, which were validated through RT-qPCR. The miRNA-mRNA network implicated hsa-miR-185-5p as diagnostic targets and drug-gene network showed colchicine, fenofibrate as potential therapeutic drugs, respectively.ConclusionThis study demonstrates that PAT is mainly associated with the occurrence of CAD following the dysfunction of immune and inflammatory processes. The identified hubgenes, predicted drugs and miRNAs are promising biomarkers and therapeutic targets for CAD.

Pericardial Adipose Tissue–Derived Leptin Promotes Myocardial Apoptosis in High‐Fat Diet–Induced Obese Rats Through Janus Kinase 2/Reactive Oxygen Species/Na+/K+‐ATPase Signaling Pathway

Background Pathophysiologic mechanisms underlying cardiac structural and functional changes in obesity are complex and linked to adipocytokines released from pericardial adipose tissue (PAT) and cardiomyocyte apoptosis. Although leptin is involved in various pathological conditions, its role in paracrine action of pericardial adipose tissue on myocardial apoptosis remains unknown. This study was designed to investigate the role of PAT‐derived leptin on myocardial apoptosis in high‐fat diet–induced obese rats. Methods and Results Hearts were isolated from lean or high‐fat diet–induced obese Wistar rats for myocardial remodeling studies. Obese rats had abnormal myocardial structure, diastolic dysfunction, greatly elevated cardiac apoptosis, enhanced cardiac fibrosis, and increased oxidative stress level. ELISA detected significantly higher than circulating leptin level in PAT of obese, but not lean, rats. Western blot and immunohistochemical analyses demonstrated increased leptin receptor density in obese hearts. H9c2 cardiomyoblasts, after being exposed to PAT‐conditioned medium of obese rats, exhibited pronounced reactive oxygen species–mediated apoptosis, which was partially reversed by leptin antagonist. Moreover, leptin derived from PAT of obese rats inhibited Na + /K + ‐ATPase activity of H9c2 cells through stimulating reactive oxygen species, thereby activating calcium‐dependent apoptosis. Pretreatment with specific inhibitors revealed that Janus kinase 2/signal transducer and activator of transcription 3 and phosphoinositide 3‐kinase/protein kinase B signaling pathways were involved in leptin‐induced myocardial apoptosis. Conclusions PAT‐derived leptin induces myocardial apoptosis in high‐fat diet–induced obese rats via activating Janus kinase 2/signal transducer and activator of transcription 3/reactive oxygen species signaling pathway and inhibiting its downstream Na + /K + ‐ATPase activity.

Increased Pericardial Adipose Tissue in Smokers

Background: Pericardial adipose tissue (PAT), a visceral fat depot directly located to the heart, is associated with atherosclerotic and inflammatory processes. The extent of PAT is related to the prevalence of coronary heart disease and might be used for cardiovascular risk prediction. This study aimed to determine the effect of smoking on the extent of PAT. Methods: We retrospectively examined 1217 asymptomatic patients (490 females, age 58.3 ± 8.3 years, smoker n = 573, non-smoker n = 644) with a multislice CT scanner and determined the PAT volume. Coronary risk factors were determined at inclusion, and a multivariate analysis was performed to evaluate the influence of smoking on PAT independent from accompanying risk factors. Results: The mean PAT volume was 215 ± 107 mL in all patients. The PAT volume in smokers was significantly higher compared to PAT volume in non-smokers (231 ± 104 mL vs. 201 ± 99 mL, p = 0.03). Patients without cardiovascular risk factors showed a significantly lower PAT volume (153 ± 155 mL, p < 0.05) compared to patients with more than 1 risk factor. Odds ratio was 2.92 [2.31, 3.61; p < 0.001] for elevated PAT in smokers. Conclusion: PAT as an individual marker of atherosclerotic activity and inflammatory burden was elevated in smokers. The finding was independent from metabolic risk factors and might therefore illustrate the increased inflammatory activity in smokers in comparison to non-smokers.

Regional Adiposity and Risk of Heart Failure and Mortality: The Jackson Heart Study

Background Visceral adipose tissue (VAT) is associated with incident heart failure (HF) and HF with preserved ejection fraction, yet it is unknown how pericardial and abdominal adiposity affect HF and mortality risks in Black individuals. We examined the associations of pericardial adipose tissue (PAT), VAT, and subcutaneous adipose tissue (SAT) with incident HF hospitalization and all‐cause mortality in a large community cohort of Black participants. Methods and Results Among the 2882 Jackson Heart Study Exam 2 participants without prevalent HF who underwent body computed tomography, we used Cox proportional hazards models to examine associations between computed tomography–derived regional adiposity and incident HF hospitalization and all‐cause mortality. Fully adjusted models included demographics and cardiovascular disease risk factors. Median follow‐up was 10.6 years among participants with available VAT (n=2844), SAT (n=2843), and PAT (n=1386). Fully adjusted hazard ratios (95% CIs) of distinct computed tomography–derived adiposity measures (PAT per 10 cm 3 , VAT or SAT per 100 cm 3 ) were as follows: for incident HF, PAT 1.08 (95% CI, 1.02–1.14) and VAT 1.04 (95% CI, 1.01–1.08); for HF with preserved ejection fraction, PAT 1.13 (95% CI, 1.04–1.21) and VAT 1.07 (95% CI, 1.01–1.13); for mortality, PAT 1.07 (95% CI, 1.03–1.12) and VAT 1.01 (95% CI, 0.98–1.04). SAT was not associated with either outcome. Conclusions High PAT and VAT, but not SAT, were associated with incident HF and HF with preserved ejection fraction, and only PAT was associated with mortality in the fully adjusted models in a longitudinal community cohort of Black participants. Future studies may help understand whether changes in regional adiposity improves HF, particularly HF with preserved ejection fraction, risk predictions. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT00005485.

Automated Quality-Controlled Cardiovascular Magnetic Resonance Pericardial Fat Quantification Using a Convolutional Neural Network in the UK Biobank

Background: Pericardial adipose tissue (PAT) may represent a novel risk marker for cardiovascular disease. However, absence of rapid radiation-free PAT quantification methods has precluded its examination in large cohorts.Objectives: We developed a fully automated quality-controlled tool for cardiovascular magnetic resonance (CMR) PAT quantification in the UK Biobank (UKB).Methods: Image analysis comprised contouring an en-bloc PAT area on four-chamber cine images. We created a ground truth manual analysis dataset randomly split into training and test sets. We built a neural network for automated segmentation using a Multi-residual U-net architecture with incorporation of permanently active dropout layers to facilitate quality control of the model's output using Monte Carlo sampling. We developed an in-built quality control feature, which presents predicted Dice scores. We evaluated model performance against the test set (n = 87), the whole UKB Imaging cohort (n = 45,519), and an external dataset (n = 103). In an independent dataset, we compared automated CMR and cardiac computed tomography (CCT) PAT quantification. Finally, we tested association of CMR PAT with diabetes in the UKB (n = 42,928).Results: Agreement between automated and manual segmentations in the test set was almost identical to inter-observer variability (mean Dice score = 0.8). The quality control method predicted individual Dice scores with Pearson r = 0.75. Model performance remained high in the whole UKB Imaging cohort and in the external dataset, with medium–good quality segmentation in 94.3% (mean Dice score = 0.77) and 94.4% (mean Dice score = 0.78), respectively. There was high correlation between CMR and CCT PAT measures (Pearson r = 0.72, p-value 5.3 ×10−18). Larger CMR PAT area was associated with significantly greater odds of diabetes independent of age, sex, and body mass index.Conclusions: We present a novel fully automated method for CMR PAT quantification with good model performance on independent and external datasets, high correlation with reference standard CCT PAT measurement, and expected clinical associations with diabetes.