Role of Epicardial Adipose Tissue in Cardiovascular Diseases: A Review.
Michał KonwerskiAleksandra GaseckaGrzegorz OpolskiMarcin GrabowskiTomasz MazurekPublished in: Biology (2022)
Cardiovascular diseases (CVDs) are the leading causes of death worldwide. Epicardial adipose tissue (EAT) is defined as a fat depot localized between the myocardial surface and the visceral layer of the pericardium and is a type of visceral fat. EAT is one of the most important risk factors for atherosclerosis and cardiovascular events and a promising new therapeutic target in CVDs. In health conditions, EAT has a protective function, including protection against hypothermia or mechanical stress, providing myocardial energy supply from free fatty acid and release of adiponectin. In patients with obesity, metabolic syndrome, or diabetes mellitus, EAT becomes a deleterious tissue promoting the development of CVDs. Previously, we showed an adverse modulation of gene expression in pericoronary adipose tissue in patients with coronary artery disease (CAD). Here, we summarize the currently available evidence regarding the role of EAT in the development of CVDs, including CAD, heart failure, and atrial fibrillation. Due to the rapid development of the COVID-19 pandemic, we also discuss data regarding the association between EAT and the course of COVID-19. Finally, we present the potential therapeutic possibilities aiming at modifying EAT's function. The development of novel therapies specifically targeting EAT could revolutionize the prognosis in CVDs.
Keyphrases
- adipose tissue
- insulin resistance
- metabolic syndrome
- cardiovascular disease
- cardiovascular events
- heart failure
- gene expression
- high fat diet
- coronary artery disease
- fatty acid
- atrial fibrillation
- left ventricular
- coronavirus disease
- mental health
- cardiac arrest
- sars cov
- cardiovascular risk factors
- brain injury
- high fat diet induced
- emergency department
- weight loss
- skeletal muscle
- venous thromboembolism
- big data
- physical activity
- social media
- machine learning
- glycemic control
- health information
- quantum dots
- acute coronary syndrome
- data analysis