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Transcriptomic and Proteomic Analysis of the Epicardial Adipose Tissue

  • Vladimir Camarena
  • David W. Sant
  • Tyler C. Huff
  • Gaofeng WangEmail author
Chapter
  • 32 Downloads
Part of the Contemporary Cardiology book series (CONCARD)

Abstract

The study of epicardial adipose tissue (EAT) has been limited by its accessibility due to its proximity to the heart. Moreover, many common animal models do not have EAT, leaving its functional role underestimated and poorly elucidated. Recent advances in medicine and science have allowed for better studies that provide a more comprehensive understanding of its physiological role. One way to dissect its function is the study of its gene expression. In this chapter, we summarize transcriptomic and proteomic analyses which show that EAT expresses a unique set of genes setting it apart from other adipose tissues in the body. This distinctive set of genes modulates a feedback mechanism that has direct interaction with the myocardium. The EAT shares its blood supply with the coronary arteries and innervation with the cardiac muscle, provides physical protection, and regulates energetic metabolites needed by the myocardium. Transcriptomic and proteomic studies show that it is a local source of adipokines with paracrine influence on the myocardium due to the intimate microcirculation shared by both tissues. These analyses also show that it has a role in the immune and endocrine systems affecting the rest of the body. Furthermore, regulation of EAT gene expression is not monolithic and can be affected by multiple factors such as sex, age, underling disease, medication, etc. Gene expression studies can therefore provide great insight into the function of EAT and its role in health and disease.

Keywords

Epicardial adipose tissue Transcriptome Proteome Adipokines Gene expression, high-throughput sequencing Secretome 

Notes

Acknowledgments

We apologize to colleagues whose works we were not able to cite here due to space limitations. The work on the EAT transcriptome in the Wang Lab is supported by the grant R01NS089525 from the National Institutes of Health.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Vladimir Camarena
    • 1
  • David W. Sant
    • 2
  • Tyler C. Huff
    • 1
  • Gaofeng Wang
    • 3
    Email author
  1. 1.John P. Hussman Institute for Human Genomics, Department of Human GeneticsUniversity of Miami Miller School of MedicineMiamiUSA
  2. 2.Biomedical Informatics, Department of Biological EngineeringUtah State UniversitySalt Lake CityUSA
  3. 3.John P. Hussman Institute for Human Genomics, Dr. John T. Macdonald Foundation Department of Human Genetics, Sylvester Comprehensive Cancer CenterMiller School of Medicine, University of MiamiMiamiUSA

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