The DOI matches its Crossref record; 93 of the 94 references it cites were found in a registry or an index.
Alterations of the microRNA network cause neurodegenerative disease
Abstract
Brain development crucially depends on the integrity of microRNA (miRNA) pathways, which function at the post-transcriptional level as a rheostat of the transcriptome and proteome of the cell. miRNAs are also involved in many other, more specific, aspects of neuronal function such as neurite outgrowth and synapse formation. Complete loss of miRNA expression in the brain leads to neurodegeneration in several animal models. Evidence from patient material is emerging that miRNA dysregulation could, indeed, contribute to neurodegenerative disorders. The translation of proteins previously implicated in familial forms of disease seems to be under control of miRNAs, and changes in miRNAs might explain how these proteins become affected in sporadic neurodegenerative disease. Thus, miRNAs are moving rapidly center stage as key regulators of neuronal development and function in addition to important contributors to neurodegenerative disorder.
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In the citing paper
“In previous study, miR-106b significantly decreased APP levels in HeLa cervical cancer cell line (Hebert et al., 2009).”
From miR-106b impairs cholesterol efflux and increases Aβ levels by repressing ABCA1 expression (2012) · cites this paper as Hebert et al., 2009
In the citing paper
“Interestingly, miR-106b levels were significantly decreased in brains of AD cases and AD mouse model (Hebert et al., 2009; Wang et al., 2011; Wang et al., 2009).”
From miR-106b impairs cholesterol efflux and increases Aβ levels by repressing ABCA1 expression (2012) · cites this paper as Hebert et al., 2009
In the citing paper
“Most interestingly, APP is another miR-106b target gene.”
From miR-106b impairs cholesterol efflux and increases Aβ levels by repressing ABCA1 expression (2012) · cites this paper as Hebert et al., 2009
Citations
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1 retracted
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RetractedThe C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14
Lee, R. C., Feinbaum, R. L., & Ambros, V. (1993) · Cell · doi:10.1016/0092-8674(93)90529-y · Cited by 12,948
Identification of Novel Genes Coding for Small Expressed RNAs
Lagos-Quintana, M., Rauhut, R., Lendeckel, W., & Tuschl, T. (2001) · Science · doi:10.1126/science.1064921 · Cited by 4,956
MicroRNA genes are transcribed by RNA polymerase II
Lee, Y., Kim, M., Han, J., Yeom, K.-H., Lee, S., Baek, S. H., & Kim, V. N. (2004) · The EMBO Journal · doi:10.1038/sj.emboj.7600385 · Cited by 4,556
Alzheimer's Disease Is a Synaptic Failure
Selkoe, D. J. (2002) · Science · doi:10.1126/science.1074069 · Cited by 4,420
α-Synuclein Locus Triplication Causes Parkinson's Disease
Singleton, A. B., Farrer, M., Johnson, J., Singleton, A., Hague, S., Kachergus, J., Hulihan, M., Peuralinna, T., Dutra, A., Nussbaum, R., et al. (2003) · Science · doi:10.1126/science.1090278 · Cited by 4,383
Silencing of microRNAs in vivo with ‘antagomirs’
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RAS Is Regulated by the let-7 MicroRNA Family
Johnson, S., Großhans, H., Shingara, J., Byrom, M., JARVIS, R., Cheng, A., Labourier, E., Reinert, K. L., Brown, D., & Slack, F. J. (2005) · Cell · doi:10.1016/j.cell.2005.01.014 · Cited by 3,699
The Microprocessor complex mediates the genesis of microRNAs
Gregory, R. I., Yan, K.-P., Amuthan, G., Chendrimada, T. P., Doratotaj, B., Cooch, N. S., & Shiekhattar, R. (2004) · Nature · doi:10.1038/nature03120 · Cited by 2,851
Cited by
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The MicroRNA Spectrum in 12 Body Fluids
Weber, J. A., Baxter, D. H., Zhang, S., Huang, D. Y., How Huang, K., Jen Lee, M., Galas, D. J., & Wang, K. (2010) · Clinical Chemistry · doi:10.1373/clinchem.2010.147405 · Cited by 2,477
Mogilyansky, E., & Rigoutsos, I. (2013) · Cell Death & Differentiation · doi:10.1038/cdd.2013.125 · Cited by 889
MicroRNA as Biomarkers and Diagnostics
Wang, J., Chen, J., & Sen, S. (2016) · Journal of Cellular Physiology · doi:10.1002/jcp.25056 · Cited by 793
Basic mechanisms of neurodegeneration: a critical update
Jellinger, K. A. (2010) · Journal of Cellular and Molecular Medicine · doi:10.1111/j.1582-4934.2010.01010.x · Cited by 640
Junker, A., Krumbholz, M., Eisele, S., Mohan, H., Augstein, F., Bittner, R., Lassmann, H., Wekerle, H., Hohlfeld, R., & Meinl, E. (2009) · Brain · doi:10.1093/brain/awp300 · Cited by 595
Metadata
- Authors
- Hébert, S. S., & De Strooper, B.
- Affiliations
- Vlaams Instituut voor Biotechnologie (BE)
- ORCID
- Hébert, Sébastien S.
- Venue
- Trends in Neurosciences
- Publisher
- Elsevier BV
- Published
- 2009-04
- Volume
- 32
- Issue
- 4
- Pages
- 199-206
- ISSN
- 0166-2236 (ISSN-L)
- OpenAlex
- W2041945875
- Cited by
- 452
- References
- 94
- Citations by year
- 2026: 11 · 2025: 9 · 2024: 10 · 2023: 16 · 2022: 18 · 2021: 17 · 2020: 26 · 2019: 26 · 2018: 26 · 2017: 19 · 2016: 37 · 2015: 38 · 2014: 26 · 2013: 39 · 2012: 33
- FWCI
- 2.82
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Trends in Neurosciences (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Lirias (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- microRNA, neurodegenerative diseases, microRNA dysregulation, post-transcriptional regulation, neuronal development, neurite outgrowth, synaptogenesis, familial neurodegenerative disease
- MeSH terms
- Animals, Humans, Models, Biological, Neurodegenerative Diseases, MicroRNAs, Gene Regulatory Networks
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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