Epicardial Adipose Tissue and Cardiovascular Health

Epicardial adipose tissue (EAT) is a specialised visceral fat depot that envelops the myocardium and lies between the visceral pericardium and the heart muscle. In physiological states, EAT contributes to thermoregulation, mechanical protection and local energy supply, while secreting adipokines that modulate myocardial metabolism. In pathological settings, EAT expansion and inflammatory remodelling have been linked to coronary artery disease, atrial fibrillation, heart failure and metabolic syndrome. Quantification of EAT by imaging modalities such as computed tomography, magnetic resonance and echocardiography provides insight into its role as a biomarker of cardiometabolic risk. Recent advances in machine learning permit rapid and reproducible segmentation of EAT, enhancing risk stratification. At the molecular level, EAT‐derived cytokines, chemokines and microRNAs exert paracrine influences on adjacent myocardium and coronary vasculature, contributing to oxidative stress, endothelial dysfunction and fibrotic remodelling. Therapeutic interventions—including lifestyle measures, metabolic drugs and precision molecular targeting—have demonstrated the potential to reduce EAT volume or modify its inflammatory profile. Understanding EAT biology and its interactions with cardiac tissue offers opportunities for improved prediction, prevention and treatment of cardiovascular disease on a global scale.

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Epicardial Adipose Tissue and Cardiovascular Health publication trend

The graph below shows the total number of articles in epicardial adipose tissue and cardiovascular health across all publications each year (not limited to Nature Index journals).

Technical terms

Epicardial adipose tissue: Visceral fat depot located between the myocardium and visceral pericardium that exerts local paracrine and mechanical effects on the heart.

CT attenuation: Quantitative measure of tissue density on computed tomography, expressed in Hounsfield units, used to characterise fat composition.

Deep learning segmentation: Artificial intelligence technique employing neural networks to automatically delineate anatomical structures in medical images.

MicroRNA: Small non-coding RNA molecules that regulate gene expression post-transcriptionally, influencing cellular pathways.

Glucagon-like peptide-1 receptor agonist (GLP-1 RA): Class of drugs that mimic incretin hormones to enhance insulin secretion and promote weight loss.

Sodium–glucose co-transporter 2 inhibitor (SGLT2 inhibitor): Antidiabetic agent that blocks renal glucose reabsorption, with secondary effects on cardiovascular risk factors and adiposity.

References

1. AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging. npj Digital Medicine (2024).
2. Role of Human Epicardial Adipose Tissue–Derived miR-92a-3p in Myocardial Redox State. Journal of the American College of Cardiology (2023).
3. Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography Implications for Cardiovascular Risk Prediction. JACC Cardiovascular Imaging (2023).
4. Efficacy of cardiometabolic drugs in reduction of epicardial adipose tissue: a systematic review and meta-analysis. Cardiovascular Diabetology (2023).