Inflammasome-driven catecholamine catabolism in macrophages blunts lipolysis during ageing
Open accessAbstract
Catecholamine-induced lipolysis, the first step in the generation of energy substrates by the hydrolysis of triglycerides, declines with age. The defect in the mobilization of free fatty acids in the elderly is accompanied by increased visceral adiposity, lower exercise capacity, failure to maintain core body temperature during cold stress, and reduced ability to survive starvation. Although catecholamine signalling in adipocytes is normal in the elderly, how lipolysis is impaired in ageing remains unknown. Here we show that adipose tissue macrophages regulate the age-related reduction in adipocyte lipolysis in mice by lowering the bioavailability of noradrenaline. Unexpectedly, unbiased whole-transcriptome analyses of adipose macrophages revealed that ageing upregulates genes that control catecholamine degradation in an NLRP3 inflammasome-dependent manner. Deletion of NLRP3 in ageing restored catecholamine-induced lipolysis by downregulating growth differentiation factor-3 (GDF3) and monoamine oxidase A (MAOA) that is known to degrade noradrenaline. Consistent with this, deletion of GDF3 in inflammasome-activated macrophages improved lipolysis by decreasing levels of MAOA and caspase-1. Furthermore, inhibition of MAOA reversed the age-related reduction in noradrenaline concentration in adipose tissue, and restored lipolysis with increased levels of the key lipolytic enzymes adipose triglyceride lipase (ATGL) and hormone sensitive lipase (HSL). Our study reveals that targeting neuro-immunometabolic signalling between the sympathetic nervous system and macrophages may offer new approaches to mitigate chronic inflammation-induced metabolic impairment and functional decline.
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Monocytes and tissue-resident macrophages are predominant producers of SASP factors such as IL-1α, IL-1β, IL-6, TNF, and HMGB1.
“Studies have shown that immune cells, including monocytes and tissue-resident macrophages, are the predominant producers of SASP factors such as IL-1α, IL-1β, IL-6, TNF and HMGB1 (refs. 75–78).”
From SenNet recommendations for detecting senescent cells in different tissues (2024) · cites this paper as [77]
The Main Text reports Il1b gene expression in bone-marrow-derived macrophages, and Extended Data Figure 7 examines senescence-associated genes in adipose-tissue macrophages. These findings support a limited link between macrophages, IL-1β and senescence-related changes, but do not establish that monocytes or tissue-resident macrophages are the predominant producers of the listed SASP factors. (LLM, conf=0.81)
Experimental — accuracy not yet measuredInflammaging is driven in part by NLRP3 inflammasome activation.
“Inflammaging is driven in part by NLRP3 inflammasome activation,5–8”
From Taurine lowers inflammaging by regulating the NLRP3 inflammasome in macrophages (2026) · cites this paper as [5]
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106 · see citing works
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · see citing works
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
Robust enumeration of cell subsets from tissue expression profiles
Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., Hoang, C. D., Diehn, M., & Alizadeh, A. A. (2015) · Nature Methods · doi:10.1038/nmeth.3337 · Cited by 13,105 · see citing works
Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., & Salzberg, S. L. (2013) · Genome Biology · doi:10.1186/gb-2013-14-4-r36 · Cited by 12,668 · see citing works
Inflammation and metabolic disorders
Hotamisligil, G. S. (2006) · Nature · doi:10.1038/nature05485 · Cited by 9,199 · see citing works
Inflammation and insulin resistance
Shoelson, S. E. (2006) · Journal of Clinical Investigation · doi:10.1172/jci29069 · Cited by 4,769 · see citing works
Cellular senescence: when bad things happen to good cells
Campisi, J., & d'Adda di Fagagna, F. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2233 · Cited by 4,441 · see citing works
Gene Ontology Consortium: going forward
The Gene Ontology Consortium (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1179 · Cited by 3,492 · see citing works
Cryopyrin activates the inflammasome in response to toxins and ATP
Mariathasan, S., Weiss, D. S., Newton, K., McBride, J., O'Rourke, K., Roose-Girma, M., Lee, W. P., Weinrauch, Y., Monack, D. M., & Dixit, V. M. (2006) · Nature · doi:10.1038/nature04515 · Cited by 3,080 · see citing works
Inflammatory links between obesity and metabolic disease
Lumeng, C. N., & Saltiel, A. R. (2011) · Journal of Clinical Investigation · doi:10.1172/jci57132 · Cited by 2,319 · see citing works
Quantification of mRNA using real-time RT-PCR
Nolan, T., Hands, R. E., & Bustin, S. A. (2006) · Nature Protocols · doi:10.1038/nprot.2006.236 · Cited by 2,247 · see citing works
Transcriptome-Based Network Analysis Reveals a Spectrum Model of Human Macrophage Activation
Xue, J., Schmidt, S. V., Sander, J., Draffehn, A., Krebs, W., Quester, I., De Nardo, D., Gohel, T. D., Emde, M., Schmidleithner, L., et al. (2014) · Immunity · doi:10.1016/j.immuni.2014.01.006 · Cited by 2,210 · see citing works
Self-citationTissue-Resident Macrophage Enhancer Landscapes Are Shaped by the Local Microenvironment
Lavin, Y., Winter, D., Blecher-Gonen, R., David, E., Keren-Shaul, H., Merad, M., Jung, S., & Amit, I. (2014) · Cell · doi:10.1016/j.cell.2014.11.018 · Cited by 2,167 · see citing works
The therapeutic potential of monoamine oxidase inhibitors
Youdim, M. B. H., Edmondson, D. E., & Tipton, K. F. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1883 · Cited by 1,374 · see citing works
MONOAMINE OXIDASE: From Genes to Behavior
Shih, J. C., Chen, K., & Ridd, M. J. (1999) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.22.1.197 · Cited by 1,211 · see citing works
Identification of White Adipocyte Progenitor Cells In Vivo
Rodeheffer, M. S., Birsoy, K., & Friedman, J. M. (2008) · Cell · doi:10.1016/j.cell.2008.09.036 · Cited by 945 · see citing works
Self-citationSchweiger, M., Schreiber, R., Haemmerle, G., Lass, A., Fledelius, C., Jacobsen, P., Tornqvist, H. E., Zechner, R., & Zimmermann, R. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m608048200 · Cited by 728 · see citing works
Canonical Nlrp3 Inflammasome Links Systemic Low-Grade Inflammation to Functional Decline in Aging
Youm, Y.-H., Grant, R. W., McCabe, L. R., Albarado, D. C., Nguyen, K. Y., Ravussin, A., Pistell, P., Newman, S., Carter, R., Laque, A., et al. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2013.09.010 · Cited by 674 · see citing works
Self-citationLocal Proliferation of Macrophages Contributes to Obesity-Associated Adipose Tissue Inflammation
Amano, S. U., Cohen, J. L., Vangala, P., Tencerová, M., Nicoloro, S. M. C., Yawe, J. C., Shen, Y., Czech, M., & Aouadi, M. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2013.11.017 · Cited by 613 · see citing works
Characterization of the adipocyte cellular lineage in vivo
Berry, R., & Rodeheffer, M. S. (2013) · Nature Cell Biology · doi:10.1038/ncb2696 · Cited by 542 · see citing works
Self-citationXu, X., Grijalva, A., Skowronski, A., van Eijk, M., Serlie, M. J., & Ferrante, A. W. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2013.11.001 · Cited by 523 · see citing works
Tăcutu, R., Craig, T., Budovsky, A., Wuttke, D., Lehmann, G., Toren, D., Cósta, J., Fraifeld, V. E., & de Magalhães, J. P. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1155 · Cited by 516 · see citing works
Network visualization and analysis of gene expression data using BioLayout Express3D
Theocharidis, A., van Dongen, S., Enright, A. J., & Freeman, T. C. (2009) · Nature Protocols · doi:10.1038/nprot.2009.177 · Cited by 453 · see citing works
Biochemistry and pathophysiology of intravascular and intracellular lipolysisPreprint
Young, S. G., & Zechner, R. (2013) · Genes & Development · doi:10.1101/gad.209296.112 · Cited by 344 · see citing works
The immune cells in adipose tissue
Ferrante, A. W. (2013) · Diabetes Obesity and Metabolism · doi:10.1111/dom.12154 · Cited by 306 · see citing works
Kr, F., Doerrler, W. T., Dinarello, C. A., Fiers, W., & Grünfeld, C. (1992) · Endocrinology · doi:10.1210/endo.130.1.1370149 · Cited by 197 · see citing works
Aging leads to a programmed loss of brown adipocytes in murine subcutaneous white adipose tissue
Rogers, N. H., Landa, A., Park, S., & Smith, R. G. (2012) · Aging Cell · doi:10.1111/acel.12010 · Cited by 171 · see citing works
Age-Associated Loss of Lamin-B Leads to Systemic Inflammation and Gut Hyperplasia
Chen, H., Zheng, X., & Zheng, Y. (2014) · Cell · doi:10.1016/j.cell.2014.10.028 · Cited by 168 · see citing works
Mowers, J. C., Uhm, M., Reilly, S. M., Simon, J., Leto, D. E., Chiang, S.-H., Chang, L. C., & Saltiel, A. R. (2013) · eLife · doi:10.7554/elife.01119 · Cited by 149 · see citing works
Catecholamine-induced lipolysis in adipose tissue of the elderly.
Lönnqvist, F., Nyberg, B., Wahrenberg, H., & Arner, P. (1990) · Journal of Clinical Investigation · doi:10.1172/jci114612 · Cited by 143 · see citing works
Elsworth, J. D., Deutch, A. Y., Redmond, D. E., et al. (1989) · Neuroscience · doi:10.1016/0306-4522(89)90212-1 · Cited by 128 · see citing works
Self-citationAndersson, O., Korach-André, M., Reissmann, E., Ibáñez, C. F., & Bertolino, P. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800272105 · Cited by 126 · see citing works
Berry, R., CHURCH, C. D., Gericke, M. T., Jeffery, E. C., Colman, L., & Rodeheffer, M. S. (2014) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-411619-1.00004-5 · Cited by 123 · see citing works
Self-citationSpadaro, O., Goldberg, E. L., Camell, C. D., Youm, Y., Kopchick, J. J., Nguyen, K., Bartke, A., Sun, L. Y., & Dixit, V. D. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.01.044 · Cited by 96 · see citing works
Self-citationAdipocyte ALK7 links nutrient overload to catecholamine resistance in obesity
Guo, T., Mármol, P., Moliner, A., Björnholm, M., Zhang, C., Shokat, K. M., & Ibáñez, C. F. (2014) · eLife · doi:10.7554/elife.03245 · Cited by 81 · see citing works
Yogosawa, S., Mizutani, S., Ogawa, Y., & Izumi, T. (2012) · Diabetes · doi:10.2337/db12-0295 · Cited by 72 · see citing works
Shen, J. J., Huang, L., Li, L., Jorgez, C. J., Matzuk, M. M., & Brown, C. (2008) · Molecular Endocrinology · doi:10.1210/me.2007-0322 · Cited by 59 · see citing works
Self-citationCzimmerer, Z., Varga, T., Póliska, S., Német, I., Szántó, A., & Nagy, L. (2012) · Immunobiology · doi:10.1016/j.imbio.2012.08.270 · Cited by 50 · see citing works
Action of Food Restriction on Age-related Changes in Adipocyte Lipolysis
Bertrand, H. A., Anderson, W. R., Masoro, E. J., et al. (1987) · Journal of Gerontology · doi:10.1093/geronj/42.6.666 · Cited by 27 · see citing works
Vega, A. P., Chacón, P., Monteseirı́n, J., et al. (2004) · Journal of Leukocyte Biology · doi:10.1189/jlb.1003459 · Cited by 25 · see citing works
Accumulation of norepinephrine by macrophages and relationships to known uptake processes.
Balter, N. J., & Schwartz, S. L. (1977) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1016/s0022-3565(25)30902-x · Cited by 25 · see citing works
Lipolysis of human adipose tissue cells: influence of donor factors.
James, R. C., Burns, T. W., & Chase, G. R. (1971) · PubMed · Cited by 21 · see citing works
Lack of an Effect of Age on -Adrenoceptor--Mediated Lipolysis in Isolated Human Adipocytes
Gerber, J. G., Detmar-Hanna, D., & Zahniser, N. R. (1999) · The Journals of Gerontology Series A · doi:10.1093/gerona/54.2.b71 · Cited by 12 · see citing works
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SenNet recommendations for detecting senescent cells in different tissues
Suryadevara, V., Hudgins, A. D., Rajesh, A., Pappalardo, A., Karpova, A., Dey, A. K., Hertzel, A., Agudelo, A., Rocha, A., Soygur, B., et al. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00738-8 · Cited by 408 · see citing works
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Villarroya, F., Cereijo, R., Villarroya, J., Gavaldà-Navarro, A., & Giralt, M. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.04.006 · Cited by 198 · see citing works
Christoffersen, B. Ø., Sanchez‐Delgado, G., John, L. M., Ryan, D. H., Raun, K., & Ravussin, E. (2022) · Obesity · doi:10.1002/oby.23374 · Cited by 142 · see citing works
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Larabee, C. M., Neely, O. C., & Domingos, A. I. (2020) · Nature Reviews Endocrinology · doi:10.1038/s41574-019-0283-6 · Cited by 123 · see citing works
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Blaszkiewicz, M., Willows, J. W., Dubois, A. L., Waible, S., DiBello, K., Lyons, L. L., Johnson, C. P., Paradie, E., Banks, N., Motyl, K., et al. (2019) · PLOS ONE · doi:10.1371/journal.pone.0221766 · Cited by 87 · see citing works
Camporez, J. P., Lyu, K., Goldberg, E. L., Zhang, D., Cline, G. W., Jurczak, M. J., Dixit, V. D., Petersen, K. F., & Shulman, G. I. (2019) · The Journal of Physiology · doi:10.1113/jp277270 · Cited by 71 · see citing works
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Self-citation
- Authors
- Camell, C. D., Sander, J., Spadaro, O., Lee, A., Nguyen, K. Y., Wing, A., Goldberg, E. L., Youm, Y.-H., Brown, C. W., Elsworth, J., Rodeheffer, M. S., Schultze, J. L., & Dixit, V. D.
- Affiliations
- Yale University (US)
- University of Bonn (DE)
- University of Tennessee Health Science Center (US)
- Corresponding author
- Dixit, Vishwa Deep
- ORCID
- Venue
- Nature
- Published
- 2017-09-27
- Volume
- 550
- Issue
- 7674
- Pages
- 119-123
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5718149
- OpenAlex
- W2757837983
- Cited by
- 456
- References
- 45
- Citations by year
- 2026: 34 · 2025: 53 · 2024: 52 · 2023: 54 · 2022: 63 · 2021: 60 · 2020: 54 · 2019: 40 · 2018: 39 · 2017: 6
- FWCI
- 28.14
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DZNE Pub (submittedVersion)
- Funders
- National Institute on Aging (R01AG048918, R01AG043608, P01AG051459)
- National Institute of General Medical Sciences (T32GM007223)
- National Institute of Allergy and Infectious Diseases (R56AI105097, R01AI105097, T32AI007019)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01AR070811)
- Topics
- Health Sciences › Medicine › Physiology › Adipose Tissue and Metabolism
- Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Lipid metabolism and biosynthesis
- Keywords
- aging, lipolysis, NLRP3 inflammasome, adipose tissue macrophages, norepinephrine, GDF3, monoamine oxidase A, caspase-1, adipose triglyceride lipase, hormone-sensitive lipase, visceral fat, free fatty acid mobilization, energy metabolism, cold tolerance, starvation survival, exercise capacity
- MeSH terms
- NLR Family, Pyrin Domain-Containing 3 Protein, Acyltransferases, Adipose Tissue, Aging, Animals, Catecholamines, Sterol Esterase, Gene Expression Regulation, Lipase, Lipolysis, Macrophages, Monoamine Oxidase, Monoamine Oxidase Inhibitors, Norepinephrine, Adipocytes, Caspase 1, Gene Expression Profiling, Mice, Growth Differentiation Factor 3, Inflammasomes
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