# Omics Insights into Epicardial Adipose Tissue: Unravelling Its Molecular Landscape
## 3 Genomics and Transcriptomics of EAT  
Genomics and transcriptomics are complementary fields that offer comprehensive insights into the genetic makeup and gene expression dynamics of organisms. EAT genomics involves the systematic analysis of all genes within EAT, facilitated by various sequencing technologies such as DNA microarrays or next-generation sequencing (NGS). These techniques enable researchers to investigate gene mutations and identify their associated role with diseases. For instance, in the context of EAT and CVDs, genomics has led to the identification of numerous genes linked to an increased risk of cardiometabolic diseases, enhancing our understanding of its genetic basis. On the other hand, transcriptomics focuses on studying all RNA transcripts and is essential for deciphering the genetic network involved in diseases due to the variation in gene expression across tissues in general or across developmental stages of tissues in particular. By integrating genomics and transcriptomics, researchers can gain a holistic understanding of genetic variation, gene expression patterns, and their implications for health and disease. A recent study selected a number of 33 SNPs associated with CAD or atherosclerosis, from GWAS and other candidate-gene association studies, and identified the MTHFR677 polymorphism (rs1801133) as the only significant and independent predictor of a higher volume of EAT, which is known to be associated with various heart conditions. The cohort included 996 healthy subjects and also tested the importance of genetic risk scores based on SNPs of specific biological pathways as a way of predicting heart disease. Interestingly, patients with a high EAT volume presented not only a high global genetic risk score, but also high values for scores including variants associated with inflammation/oxidation and obesity/diabetes pathways, separately [35]. At the same time, another study accounted for the importance of adding an EAT volume parameter to a genetic risk score in order to better predict major adverse cardiovascular events [36]. EAT consists mainly of white adipocytes which present brown fat-like properties that unfortunately decrease with age. For example, miR-1-3p and miR-133a-3p released by EAT and considered potential targets in atrial fibrillation are also specific for brown adipose tissue and not white adipocytes, therefore suggesting the brown fat-like feature [37]. Another example is miR-455-3p expressed by EAT, which induces PPAR expression, resulting in increased expression of brown adipose tissue-specific genes [38]. miR-455-3p expression is down-regulated in CAD, leading to a reduced anti-inflammatory effect for the cardiovascular system [39]. In time, epicardial adipocytes become increasingly vulnerable to environmental, metabolic and hemodynamic influences, gradually shifting the function of EAT from thermogenesis to energy storage. However, in the case of advanced phases of CAD, we also see a suppression of brown fat-like activity within EAT. Interestingly, this process could be inversed by pharmacological enhancement of gene expression for proteins involved in the browning of adipose tissue. The positive outcome is associated with a reduction in inflammation and left ventricular mass [2]. Uncoupling protein-1 (UCP1), the main marker of brown adipose tissue, is highly expressed in EAT as opposed to other adipose tissues, suggesting a protective role in thermogenesis for the myocardium against hypothermia [14]. The mechanism by which UCP1 is involved in preserving EAT homeostasis is largely unknown, but high UCP-1 expression in EAT was linked to suppression of reactive oxygen species production and immune responses. Interestingly, a bidirectional connection between UCP-1 and adaptive immunity at the extensive transcriptome level is suggested [40].