The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
A Regulatory Role for MicroRNA 33* in Controlling Lipid Metabolism Gene Expression
Open accessAbstract
hsa-miR-33a and hsa-miR-33b, intronic microRNAs (miRNAs) located within the sterol regulatory element-binding protein 2 and 1 genes (Srebp-2 and -1), respectively, have recently been shown to regulate lipid homeostasis in concert with their host genes. Although the functional role of miR-33a and -b has been highly investigated, the role of their passenger strands, miR-33a* and -b*, remains unclear. Here, we demonstrate that miR-33a* and -b* accumulate to steady-state levels in human, mouse, and nonhuman primate tissues and share a similar lipid metabolism target gene network as their sister strands. Analogous to miR-33, miR-33* represses key enzymes involved in cholesterol efflux (ABCA1 and NPC1), fatty acid metabolism (CROT and CPT1a), and insulin signaling (IRS2). Moreover, miR-33* also targets key transcriptional regulators of lipid metabolism, including SRC1, SRC3, NFYC, and RIP140. Importantly, inhibition of either miR-33 or miR-33* rescues target gene expression in cells overexpressing pre-miR-33. Consistent with this, overexpression of miR-33* reduces fatty acid oxidation in human hepatic cells. Altogether, these data support a regulatory role for the miRNA* species and suggest that miR-33 regulates lipid metabolism through both arms of the miR-33/miR-33* duplex.
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“It represses insulin receptor substrate 2 (IRS2), protein kinase AMP-activated catalytic subunit a1 (PRKAA1), and sirtuin 6 (SIRT6) 34 , 35) , genes that are important for the maintenance of insulin sensitivity, cellular energy balance, and the mitochondrial function.”
From Critical Role of microRNA-33a/b in Cardiovascular and Metabolic Disease: Molecular Mechanisms and Therapeutic Perspectives (2026) · cites this paper as [35]
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“MiR-33 suppresses genes involved in mitochondrial β-oxidation, such as carnitine palmitoyltransferase 1A (CPT1A), hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit b (HADHB), and carnitine O-octanoyltransferase (CROT) 15 , 17 , 34 , 35) .”
From Critical Role of microRNA-33a/b in Cardiovascular and Metabolic Disease: Molecular Mechanisms and Therapeutic Perspectives (2026) · cites this paper as [35]
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Citations
Cites
MicroRNAs: Target Recognition and Regulatory Functions
Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.01.002 · Cited by 20,068
The functions of animal microRNAs
Ambros, V. (2004) · Nature · doi:10.1038/nature02871 · Cited by 10,728
(2008) · doi:10.1038/nrg2290 · Cited by 5,199
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/jci15593 · Cited by 4,794
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
Asymmetry in the Assembly of the RNAi Enzyme Complex
Schwarz, D. S., Hutvágner, G., Du, T., Xu, Z., Aronin, N., & Zamore, P. D. (2003) · Cell · doi:10.1016/s0092-8674(03)00759-1 · Cited by 2,922
Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIP
Hafner, M., Landthaler, M., Burger, L., Khorshid, M., Hausser, J., Berninger, P., Rothballer, A., Ascano, M., Jungkamp, A.-C., Munschauer, M., et al. (2010) · Cell · doi:10.1016/j.cell.2010.03.009 · Cited by 2,873
Functional siRNAs and miRNAs exhibit strand bias
Khvorova, A., Reynolds, A., & Jayasena, S. D. (2003) · Cell · doi:10.1016/s0092-8674(03)00801-8 · Cited by 2,645
Argonaute HITS-CLIP decodes microRNA–mRNA interaction maps
Chi, S. W., Zang, J. B., Mele, A., & Darnell, R. B. (2009) · Nature · doi:10.1038/nature08170 · Cited by 1,791
Dweep, H., Sticht, C., Pandey, P., & Gretz, N. (2011) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.05.002 · Cited by 1,707
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Lu, R., Lin, M., Yang, F., Jia, S., Zhang, Y., Qin, C., Meng, X., & Nie, G.-X. (2021) · Fish Physiology and Biochemistry · doi:10.1007/s10695-021-00956-3 · Cited by 6
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Horie, T., Baba, O., Nishino, T., Yamashita, Y., Tsujisaka, Y., & Ono, K. (2026) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.rv22045 · Cited by 5
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Kim, B.-G., Yuk, M., Park, M., Ryu, H., Park, J., Yu, H., Park, S. S., Hong, J. T., Lim, K., Han, S., et al. (2025) · Brain · doi:10.1093/brain/awaf244 · Cited by 4
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Mohammadi, S. (2014) · Journal of Metabolic Syndrome · doi:10.4172/2167-0943.1000158 · Cited by 4
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Sun, X., & Feinberg, M. W. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-812513-7.00010-0 · Cited by 2
Salem, M. L., Alwasel, S. H., Faris, M. E., Aldahmash, W., Sanoh, N. E., Elkomy, H. A., Khallaf, E. M., Shaheraldin, A. A., Solaiman, T., Mostafa, N., et al. (2025) · Springer eBooks · doi:10.1007/978-981-96-6783-3_11 · Cited by 1
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Chen, X., Zhou, Y., Yang, J., Xue, S., Wang, Q., Guo, X., Zhang, Y., & Niu, W. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms262210855 · Cited by 2
Hübner, M., Galante, P. A. F., Kreth, S., & Hinske, L. C. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7601-0_7 · Cited by 1
Zhou, H., Zhou, Z., Yin, Z., Lin, J., Ni, B., Wang, X., Peng, Y., & Xie, W. (2022) · Gene Reports · doi:10.1016/j.genrep.2022.101726 · Cited by 1
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Hennessy, E. J., & FitzGerald, G. A. (2020) · Journal of Clinical Investigation · doi:10.1172/jci144227 · Cited by 1
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Fujii, Y. R. (2023) · Springer eBooks · doi:10.1007/978-981-99-3165-1_4
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Soni, V., & Upadhyay, A. (2026) · Springer eBooks · doi:10.1007/978-3-031-46895-7_8
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Dongre, S., Jaiswal, A., Chaudhary, M., Soni, N., & Bissa, B. (2026) · Gene · doi:10.1016/j.gene.2026.150062
Hardy, L. M. (2019) · theses.fr (ABES) · doi:10.70675/2f5f4b0dzc92fz4cb4z9c5bzeb6d3fd3e791
Habib, M. (2022) · theses.fr (ABES) · doi:10.70675/e634ffe7zc86dz4e0fzb03dz223ee5589a93
Metadata
- Authors
- Goedeke, L., Vales-Lara, F. M., Fenstermaker, M., Cirera-Salinas, D., Chamorro-Jorganes, A., Ramírez, C. M., Mattison, J. A., de Cabo, R., Suárez, Y., & Fernández-Hernando, C.
- Affiliations
- New York University (US)
- Department of Medicine, Leon H. Charney Division of Cardiology, Department of Cell Biology, and the Marc and Ruti Bell Vascular Biology and Disease Program, New York University School of Medicine, New York, New York, USA
- National Institutes of Health (US)
- Venue
- Molecular and Cellular Biology
- Publisher
- Informa UK Limited
- Published
- 2013-06-01
- Volume
- 33
- Issue
- 11
- Pages
- 2339-2352
- ISSN
- 0270-7306 (ISSN-L)
- 1098-5549
- PMC
- PMC3648071
- OpenAlex
- W2108732038
- Cited by
- 140
- References
- 43
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 3 · 2023: 9 · 2022: 6 · 2021: 14 · 2020: 7 · 2019: 9 · 2018: 14 · 2017: 10 · 2016: 17 · 2015: 20 · 2014: 19 · 2013: 2
- FWCI
- 6.80
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Molecular and Cellular Biology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (F31AG043318)
- National Heart, Lung, and Blood Institute (R01HL105945, R01HL106063, R01HL107953)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Cholesterol and Lipid Metabolism
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
- Keywords
- miR-33a, miR-33b, miR-33, intronic microRNA, lipid metabolism, SREBP2, SREBP1, cholesterol efflux, fatty acid oxidation, insulin signaling, insulin receptor substrate 2, ABCA1, NPC1, CPT1A, SRC-1, SRC-3, RIP140, hepatocytes
- MeSH terms
- Animals, Base Sequence, Cell Line, Fatty Acids, Gene Expression Regulation, Humans, Liver, Macaca mulatta, Macrophages, Male, Mice, Inbred C57BL, Conserved Sequence, 3' Untranslated Regions, MicroRNAs, Lipid Metabolism, Mice
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