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Article
2023
NOD-like receptors - emerging links to obesity and associated morbidities
NOD-like receptors - emerging links to obesity and associated morbidities
Abstract (English)
Obesity and its associated metabolic morbidities have been and still are on the rise, posing a major challenge to health care systems worldwide. It has become evident over the last decades that a low-grade inflammatory response, primarily proceeding from the adipose tissue (AT), essentially contributes to adiposity-associated comorbidities, most prominently insulin resistance (IR), atherosclerosis and liver diseases. In mouse models, the release of pro-inflammatory cytokines such as TNF-alpha (TNF-α) and interleukin (IL)-1β and the imprinting of immune cells to a pro-inflammatory phenotype in AT play an important role. However, the underlying genetic and molecular determinants are not yet understood in detail. Recent evidence demonstrates that nucleotide-binding and oligomerization domain (NOD)-like receptor (NLR) family proteins, a group of cytosolic pattern recognition receptors (PRR), contribute to the development and control of obesity and obesity-associated inflammatory responses. In this article, we review the current state of research on the role of NLR proteins in obesity and discuss the possible mechanisms leading to and the outcomes of NLR activation in the obesity-associated morbidities IR, type 2 diabetes mellitus (T2DM), atherosclerosis and non-alcoholic fatty liver disease (NAFLD) and discuss emerging ideas about possibilities for NLR-based therapeutic interventions of metabolic diseases.
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International journal of molecular sciences, 24 (2023), 10, 8595.
https://doi.org/10.3390/ijms24108595.
ISSN: 1422-0067
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English
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610 Medicine and health
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Sustainable Development Goals
BibTeX
@article{Bauer2023,
url = {https://hohpublica.uni-hohenheim.de/handle/123456789/16254},
doi = {10.3390/ijms24108595},
author = {Bauer, Sarah and Hezinger, Lucy and Rexhepi, Fjolla et al.},
title = {NOD-like receptors - emerging links to obesity and associated morbidities},
journal = {International journal of molecular sciences},
year = {2023},
volume = {24},
number = {10},
}