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Inactivation of the E3 Ubiquitin Ligase IDOL Attenuates Diet-Induced Obesity and Metabolic Dysfunction in Mice
Abstract
Objective—: The E3 ubiquitin ligase IDOL (inducible degrader of the LDLR [LDL (low-density lipoprotein) receptor]) is a post-transcriptional regulator of LDLR abundance. Model systems and human genetics support a role for IDOL in regulating circulating LDL levels. Whether IDOL plays a broader metabolic role and affects development of metabolic syndrome-associated comorbidities is unknown. Approach and Results—: We studied WT (wild type) and Idol (−/−) (Idol-KO) mice in 2 models: physiological aging and diet-induced obesity. In both models, deletion of Idol protected mice from metabolic dysfunction. On a Western-type diet, Idol loss resulted in decreased circulating levels of cholesterol, triglycerides, glucose, and insulin. This was accompanied by protection from weight gain in short- and long-term dietary challenges, which could be attributed to reduced hepatosteatosis and fat mass in Idol-KO mice. Although feeding and intestinal fat uptake were unchanged in Idol-KO mice, their brown adipose tissue was protected from lipid accumulation and had elevated expression of UCP1 (uncoupling protein 1) and TH (tyrosine hydroxylase). Indirect calorimetry indicated a marked increase in locomotion and suggested a trend toward increased cumulative energy expenditure and fat oxidation. An increase in in vivo clearance of reconstituted lipoprotein particles in Idol-KO mice may sustain this energetic demand. In the BXD mouse genetic reference population, hepatic Idol expression correlates with multiple metabolic parameters, thus providing support for findings in the Idol-KO mice. Conclusions—: Our study uncovers an unrecognized role for Idol in regulation of whole body metabolism in physiological aging and on a Western-type diet. These findings support Idol inhibition as a therapeutic strategy to target multiple metabolic syndrome-associated comorbidities.
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Mice lacking Idol have a beneficial metabolic and plasma lipid profile, yet the effect on hepatic LDLR was limited.
“Mice lacking Idol have a beneficial metabolic and plasma lipid profile, yet the effect on hepatic LDLR was limited.”
From The low-density lipoprotein receptor: Emerging post-transcriptional regulatory mechanisms (2025) · cites this paper as [73]
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Statins and risk of incident diabetes: A collaborative meta-analysis of randomised statin trials
Sattar, N., Preiss, D., Murray, H. M., Welsh, P., Buckley, B. M., de Craen, A. J., Seshasai, S. R. K., McMurray, J. J., Freeman, D. J., Jukema, J. W., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(09)61965-6 · Cited by 2,436
Variation in PCSK9 and HMGCR and Risk of Cardiovascular Disease and Diabetes
Ference, B. A., Robinson, J. G., Brook, R. D., Catapano, A. L., Chapman, M. J., Neff, D. R., Voros, S., Giugliano, R. P., Davey Smith, G., Fazio, S., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1604304 · Cited by 743
Poirier, S., Mayer, G., Benjannet, S., Bergeron, E., Marcinkiewicz, J., Nassoury, N., Mayer, H., Nimpf, J., Prat, A., & Seidah, N. G. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m708098200 · Cited by 477
PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study
Schmidt, A. F., Swerdlow, D. I., Holmes, M. V., Patel, R. S., Fairhurst-Hunter, Z., Lyall, D. M., Hartwig, F. P., Horta, B. L., Hyppönen, E., Power, C., et al. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(16)30396-5 · Cited by 380
Brown and beige fat: Molecular parts of a thermogenic machine
Cohen, P., & Spiegelman, B. M. (2015) · Diabetes · doi:10.2337/db15-0318 · Cited by 259
Hong, C., Duit, S., Jalonen, P., Out, R., Scheer, L., Sorrentino, V., Boyadjian, R., Rodenburg, K. W., Foley, E., Korhonen, L., et al. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m110.123729 · Cited by 142
Self-citationKooijman, S., Wang, Y., Parlevliet, E. T., Boon, M. R., Edelschaap, D., Snaterse, G., Pijl, H., Romijn, J. A., & Rensen, P. C. N. (2015) · Diabetologia · doi:10.1007/s00125-015-3727-0 · Cited by 140
Self-citationThe LXR–Idol Axis Differentially Regulates Plasma LDL Levels in Primates and Mice
Hong, C., Marshall, S. M., McDaniel, A. L., Graham, M., Layne, J. D., Cai, L., Scotti, E., Boyadjian, R., Kim, J., Chamberlain, B. T., et al. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.10.001 · Cited by 87
Sorrentino, V., Nelson, J. K., Maspero, E., Marques, A. R. A., Scheer, L., Polo, S., & Zelcer, N. (2013) · Journal of Lipid Research · doi:10.1194/jlr.m037713 · Cited by 68
Self-citationWeissglas-Volkov, D., Calkin, A. C., Tusie-Luna, T., Sinsheimer, J. S., Zelcer, N., Riba, L., Tino, A. M. V., Ordoñez-Sánchez, M. L., Cruz-Bautista, I., Aguilar-Salinas, C. A., et al. (2011) · Journal of Clinical Investigation · doi:10.1172/jci45504 · Cited by 66
Self-citationChoi, J., Gao, J., Kim, J., Hong, C., Kim, J., & Tontonoz, P. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aad1904 · Cited by 49
Gao, J., Marosi, M., Choi, J., Achiro, J. M., Kim, S., Li, S., Otis, K., Martin, K. C., Portera-Cailliau, C., & Tontonoz, P. (2017) · eLife · doi:10.7554/elife.29178 · Cited by 30
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Research works printed but not linked: 27
- 10.1126/science.3513311 · DOI · Paper page
- 10.1001/jama.2015.1206 · DOI
- 10.1016/S0140-6736(12)61190-8 · DOI · Paper page
- 10.1016/j.numecd.2017.03.001 · DOI
- 10.1161/CIRCRESAHA.114.301621 · DOI
- 10.1016/j.febslet.2009.12.018 · DOI
- 10.1111/1753-0407.12139 · DOI
- 10.1126/science.1168974 · DOI · Paper page
- 10.1097/MOL.0b013e3283532947 · DOI · Paper page
- 10.1074/jbc.274.51.36288 · DOI · Paper page
- 10.1093/eurheartj/ehs472 · DOI
- 10.1038/nm0395-221 · DOI
- 10.1016/j.cell.2012.08.012 · DOI
- 10.1016/j.cell.2014.07.039 · DOI · Paper page
- 10.1097/01.CCM.0000063260.07222.76 · DOI
- 10.1194/jlr.D023788 · DOI
- 10.1038/ncomms7356 · DOI
- 10.1016/S0092-8674(00)81432-4 · DOI
- 10.1038/387090a0 · DOI · Paper page
- 10.1007/s00125-015-3594-8 · DOI
- 10.1161/ATVBAHA.108.181586 · DOI
- 10.1161/ATVBAHA.110.220988 · DOI · Paper page
- 10.1172/JCI29383 · DOI · Paper page
- 10.1194/jlr.M800027-JLR200 · DOI · Paper page
- 10.1172/JCI33296 · DOI · Paper page
- 10.2337/db11-0081 · DOI · Paper page
- 10.1038/nature09270 · DOI · Paper page
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Lee, S. D., Priest, C., Bjursell, M., Gao, J., Arneson, D. V., Ahn, I. S., Diamante, G., van Veen, J. E., Massa, M. G., Calkin, A. C., et al. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0127-7 · Cited by 26
Adi, D., Lu, X.-Y., Fu, Z.-Y., Wei, J., Baituola, G., Meng, Y.-J., Zhou, Y.-X., Hu, A., Wang, J.-K., Lu, X.-F., et al. (2019) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.119.312589 · Cited by 24
The low-density lipoprotein receptor: Emerging post-transcriptional regulatory mechanisms
Ndoj, K., Meurs, A., Papaioannou, D., Bjune, K., & Zelcer, N. (2025) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2024.119082 · Cited by 17
Self-citationSachdev, V., van Loon, N. M., Kingma, J., Ottenhoff, R., Tan, J. M. E., van den Berg, M., Duijst, S., Jongejan, A., Levels, J. H. M., Rensen, P. C. N., et al. (2026) · Molecular Metabolism · doi:10.1016/j.molmet.2026.102379 · Cited by 1
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Metadata
- Authors
- van Loon, N. M., Ottenhoff, R., Kooijman, S., Moeton, M., Scheij, S., Roscam Abbing, R. L. P., Gijbels, M. J. J., Levels, J. H. M., Sorrentino, V., Berbée, J. F. P., Rensen, P. C. N., & Zelcer, N.
- Affiliations
- From the Department of Medical Biochemistry (N.M.v.L., R.O., M.M., S.S., M.J.J.G., N.Z.)
- Academic Medical Center, University of Amsterdam, The Netherlands; Division of Endocrinology, Department of Medicine, Einthoven Laboratory for Experimental Vascular and Regenerative Medicine, Leiden University Medical Center, The Netherlands (S.K., J.F.P.B., P.C.N.R.)
- Tytgat Institute for Liver and Intestinal Research (R.L.P.R.A.)
- Department of Experimental Vascular Medicine (J.H.M.L.)
- CARIM, Maastricht University, The Netherlands; and Laboratory for Integrative and Systems Physiology, EPFL, Lausanne, Switzerland (V.S.).
- Venue
- Arteriosclerosis, Thrombosis, and Vascular Biology
- Published
- 2018-08
- Volume
- 38
- Issue
- 8
- Pages
- 1785-1795
- ISSN
- 1079-5642
- 1524-4636
- PMC
- PMC6092113
- Cited by
- 25
- References
- 12
- Language
- en
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