The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Transcriptional Regulation of Metabolism
Abstract
Our understanding of metabolism is undergoing a dramatic shift. Indeed, the efforts made towards elucidating the mechanisms controlling the major regulatory pathways are now being rewarded. At the molecular level, the crucial role of transcription factors is particularly well-illustrated by the link between alterations of their functions and the occurrence of major metabolic diseases. In addition, the possibility of manipulating the ligand-dependent activity of some of these transcription factors makes them attractive as therapeutic targets. The aim of this review is to summarize recent knowledge on the transcriptional control of metabolic homeostasis. We first review data on the transcriptional regulation of the intermediary metabolism, i.e., glucose, amino acid, lipid, and cholesterol metabolism. Then, we analyze how transcription factors integrate signals from various pathways to ensure homeostasis. One example of this coordination is the daily adaptation to the circadian fasting and feeding rhythm. This section also discusses the dysregulations causing the metabolic syndrome, which reveals the intricate nature of glucose and lipid metabolism and the role of the transcription factor PPARγ in orchestrating this association. Finally, we discuss the molecular mechanisms underlying metabolic regulations, which provide new opportunities for treating complex metabolic disorders.
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Cites
Insulin signalling and the regulation of glucose and lipid metabolism
Saltiel, A. R., & Kahn, C. R. (2001) · Nature · doi:10.1038/414799a · Cited by 5,326
Coordination of circadian timing in mammals
Reppert, S. M., & Weaver, D. R. (2002) · Nature · doi:10.1038/nature00965 · Cited by 4,379
SREBPs: activators of the complete program of cholesterol and fatty acid synthesis in the liver
Horton, J. D., Goldstein, J. L., & Brown, M. S. (2002) · Journal of Clinical Investigation · doi:10.1172/jci0215593 · Cited by 4,092
Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome
Wajchenberg, B. L. (2000) · Endocrine Reviews · doi:10.1210/edrv.21.6.0415 · Cited by 2,961
A decade of molecular biology of retinoic acid receptors
Chambon, P. (1996) · The FASEB Journal · doi:10.1096/fasebj.10.9.8801176 · Cited by 2,889
Damiola, F., Le Minh, N., Preitner, N., Kornmann, B., Fleury-Olela, F., & Schibler, U. (2000) · Genes & Development · doi:10.1101/gad.183500 · Cited by 2,394
The coregulator exchange in transcriptional functions of nuclear receptors
Glass, C. K., & Rosenfeld, M. G. (2000) · Genes & Development · doi:10.1101/gad.14.2.121 · Cited by 2,233
Braissant, O., Foufelle, F., Scotto, C., Dauça, M., & Wahli, W. (1996) · Endocrinology · doi:10.1210/endo.137.1.8536636 · Cited by 2,217
Self-citationPeroxisome-Proliferator-Activated Receptor δ Activates Fat Metabolism to Prevent Obesity
Wang, Y.-X., Lee, C.-H., Tiep, S., Yu, R. T., Ham, J., Kang, H., & Evans, R. M. (2003) · Cell · doi:10.1016/s0092-8674(03)00269-1 · Cited by 1,296
Peroxisome proliferator–activated receptor γ coactivator-1 promotes cardiac mitochondrial biogenesis
Lehman, J. J., Barger, P. M., Kovacs, A., Saffitz, J. E., Medeiros, D. M., & Kelly, D. P. (2000) · Journal of Clinical Investigation · doi:10.1172/jci10268 · Cited by 1,285
Cited by
Feige, J. N., Gelman, L., Michalik, L., Desvergne, B., & Wahli, W. (2006) · Progress in Lipid Research · doi:10.1016/j.plipres.2005.12.002 · Cited by 786
Self-citationThe randle cycle revisited: a new head for an old hat.
Hue, L., & Taegtmeyer, H. (2009) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00093.2009 · Cited by 743
Feige, J. N., Lagouge, M., Canto, C., Strehle, A., Houten, S. M., Milne, J. C., Lambert, P. D., Mataki, C., Elliott, P. J., & Auwerx, J. (2008) · Cell Metabolism · doi:10.1016/j.cmet.2008.08.017 · Cited by 719
Clark, A., & Mach, N. (2016) · Journal of the International Society of Sports Nutrition · doi:10.1186/s12970-016-0155-6 · Cited by 583
“Glutamine, a nonessential amino acid that’s the most abundant in the human body [102], is crucial not only for the glutamate and GABA synthesis but also for optimal functioning of leukocytes such as lymphocytes and macrophages, T cell proliferation and function [104], intestinal enterocytes growth [102].”
BackgroundRedox control of inflammation in macrophages
Brüne, B., Dehne, N., Grossmann, N., Jung, M., Namgaladze, D., Schmid, T., von Knethen, A., & Weigert, A. (2013) · Antioxidants & Redox Signaling · doi:10.1089/ars.2012.4785 · Cited by 377
PPAR-δ senses and orchestrates clearance of apoptotic cells to promote tolerance
Mukundan, L., Odegaard, J. I., Morel, C. R., Heredia, J. E., Mwangi, J. W., Ricardo-Gonzalez, R. R., Goh, Y. P. S., Eagle, A. R., Dunn, S. E., Awakuni, J. U. H., et al. (2009) · Nature Medicine · doi:10.1038/nm.2048 · Cited by 368
Hepatic Hdac3 promotes gluconeogenesis by repressing lipid synthesis and sequestration
Sun, Z., Miller, R. A., Patel, R. T., Chen, J., Dhir, R., Wang, H., Zhang, D., Graham, M. J., Unterman, T. G., Shulman, G. I., et al. (2012) · Nature Medicine · doi:10.1038/nm.2744 · Cited by 335
Transcriptional coregulators in the control of energy homeostasis
Feige, J. N., & Auwerx, J. (2007) · Trends in Cell Biology · doi:10.1016/j.tcb.2007.04.001 · Cited by 325
Retinoic acid synthesis and functions in early embryonic development
Kin Ting Kam, R., Deng, Y., Chen, Y., & Zhao, H. (2012) · Cell & Bioscience · doi:10.1186/2045-3701-2-11 · Cited by 283
de Wit, N. J., Bosch-Vermeulen, H., de Groot, P. J., Hooiveld, G. J., Bromhaar, M. M. G., Jansen, J., Müller, M., & van der Meer, R. (2008) · BMC Medical Genomics · doi:10.1186/1755-8794-1-14 · Cited by 182
Koliwad, S. K., Kuo, T., Shipp, L. E., Gray, N. E., Backhed, F., So, A. Y.-L., Farese, R. V., & Wang, J.-C. (2009) · Journal of Biological Chemistry · doi:10.1074/jbc.m109.025452 · Cited by 164
Nuclear receptors as therapeutic targets for Alzheimer's disease
Mandrekar-Colucci, S., & Landreth, G. E. (2011) · Expert Opinion on Therapeutic Targets · doi:10.1517/14728222.2011.594043 · Cited by 126
Nahlé, Z., Hsieh, M., Pietka, T., Coburn, C. T., Grimaldi, P. A., Zhang, M. Q., Das, D., & Abumrad, N. A. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m706478200 · Cited by 122
Beta-Aminoisobutyric Acid as a Novel Regulator of Carbohydrate and Lipid Metabolism
Tanianskii, D. A., Jarzebska, N., Birkenfeld, A. L., O’Sullivan, J. F., & Rodionov, R. N. (2019) · Nutrients · doi:10.3390/nu11030524 · Cited by 121
Epigenetic control and the circadian clock: Linking metabolism to neuronal responses
Orozco-Solis, R., & Sassone-Corsi, P. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.01.043 · Cited by 94
Roy, D., & Tedeschi, A. (2021) · Cells · doi:10.3390/cells10051078 · Cited by 68
Burg, T., Rossaert, E., Moisse, M., Van Damme, P., & Van Den Bosch, L. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222011224 · Cited by 50
Chung, K. W., Lee, E. K., Kim, D. H., An, H. J., Kim, N. D., Im, D. S., Lee, J., Yu, B. P., & Chung, H. Y. (2015) · Aging Cell · doi:10.1111/acel.12305 · Cited by 41
Tsagianni, A., Mars, W. M., Bhushan, B., Bowen, W. C., Orr, A., Stoops, J., Paranjpe, S., Tseng, G. C., Liu, S., & Michalopoulos, G. K. (2018) · The American Journal of Pathology · doi:10.1016/j.ajpath.2018.06.009 · Cited by 29
Jasinska, W., Dindo, M., Cordoba, S. M. C., Serohijos, A. W. R., Laurino, P., Brotman, Y., & Bershtein, S. (2024) · Nature Communications · doi:10.1038/s41467-024-49646-7 · Cited by 21
Ressa, A., Bosdriesz, E., de Ligt, J., Mainardi, S., Maddalo, G., Prahallad, A., Jager, M., de la Fonteijne, L., Fitzpatrick, M., Groten, S., et al. (2018) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra117.000486 · Cited by 17
Identification of the Transcription Factor ATF3 as a Direct and Indirect Regulator of the LDLR
Bauer, S., Eigenmann, J., Zhao, Y., Fleig, J., Hawe, J. S., Pan, C., Bongiovanni, D., Wengert, S., Ma, A., Lusis, A. J., et al. (2022) · Metabolites · doi:10.3390/metabo12090840 · Cited by 8
Metadata
- Authors
- Desvergne, B., Michalik, L., & Wahli, W.
- Venue
- Physiological Reviews
- Publisher
- American Physiological Society
- Published
- 2006-04
- Volume
- 86
- Issue
- 2
- Pages
- 465-514
- ISSN
- 0031-9333 (ISSN-L)
- 1522-1210
- OpenAlex
- W1968659767
- Cited by
- 892
- References
- 34
- FWCI
- 3.17
- Type
- journal article
- Language
- en
- Open access
- closed
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