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Adipokines as Novel Biomarkers in Aging and Heart Failure

  • Ken Shinmura
Chapter

Abstract

Adipokines represent a family of proteins produced in adipose tissue that affect various biological processes including metabolism, satiety, inflammation, and cardiovascular function. Adipocytes are the major cell type comprising adipose tissue. These cells secrete numerous factors, broadly termed adipokines, into the blood, including classic pro-inflammatory cytokines such as tumor necrosis factor-α and interleukin-6, acute phase proteins such as plasminogen activator inhibitor 1 and haptoglobin, and specific adipokines such as leptin, adiponectin, resistin, apelin, visfatin, lipocalin-2, omentin, chemerin, and vaspin. Since adipose tissue is highly vascularized, it is now recognized as an endocrine organ. Different adipose depots have distinct adipokine secretion profiles, which are altered in conditions of obesity, type 2 diabetes mellitus, and metabolic syndrome. Indeed, adipokines including leptin, adiponectin, and apelin exert potent and diverse cardiovascular effects that are mediated by their specific receptors and involve multifaceted cell signaling pathways. Mounting evidence demonstrates that the circulating levels of these adipokines are closely associated with the development and/or progression of cardiovascular disease including heart failure. Thus, adipokines have received considerable attention because of their potential for novel biomarkers of cardiovascular disease including heart failure. In this chapter, we discuss the biological functions and potent cardiovascular effects of the 9 above-mentioned adipokines and, then, estimate the usefulness of measuring serum levels of each adipokine as a novel biomarker of heart failure, using information from both clinical and experimental investigations.

Keywords

Heart Failure Brain Natriuretic Peptide White Adipose Tissue Adiponectin Level Nicotinamide Adenine Dinucleotide 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by a grant from the Ministry of Education, Culture, and Science, Japan (2010–2012), and by a grant from the Vehicle Racing Commemorative Foundation (2012).

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© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Division of Geriatric Medicine, Department of Internal MedicineKeio University School of MedicineShinjyuku-kuJapan

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