The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
The Long Noncoding RNA CHRF Regulates Cardiac Hypertrophy by Targeting miR-489
Open accessAbstract
Rationale: Sustained cardiac hypertrophy is often accompanied by maladaptive cardiac remodeling leading to decreased compliance and increased risk for heart failure. Maladaptive hypertrophy is considered to be a therapeutic target for heart failure. MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs) have various biological functions and have been extensively investigated in past years. Objective: We identified miR-489 and lncRNAs (cardiac hypertrophy related factor, CHRF) from hypertrophic cardiomyocytes. Here, we tested the hypothesis that miR-489 and CHRF can participate in the regulation of cardiac hypertrophy in vivo and in vitro. Methods and Results: A microarray was performed to analyze miRNAs in response to angiotensin II treatment, and we found miR-489 was substantially reduced. Enforced expression of miR-489 in cardiomyocytes and transgenic overexpression of miR-489 both exhibited reduced hypertrophic response on angiotensin II treatment. We identified myeloid differentiation primary response gene 88 (Myd88) as a miR-489 target to mediate the function of miR-489 in cardiac hypertrophy. Knockdown of Myd88 in cardiomyocytes and Myd88-knockout mice both showed attenuated hypertrophic responses. Furthermore, we explored the molecular mechanism by which miR-489 expression is regulated and found that an lncRNA that we named CHRF acts as an endogenous sponge of miR-489, which downregulates miR-489 expression levels. CHRF is able to directly bind to miR-489 and regulate Myd88 expression and hypertrophy. Conclusions: Our present study reveals a novel cardiac hypertrophy regulating model that is composed of CHRF, miR-489, and Myd88. The modulation of their levels may provide a new approach for tackling cardiac hypertrophy.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Long non-coding RNAs: insights into functions
Mercer, T. R., Dinger, M. E., & Mattick, J. S. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2521 · Cited by 5,654
The nuclear RNase III Drosha initiates microRNA processing
Lee, Y., Ahn, C., Han, J., Choi, H., Kim, J., Yim, J., Lee, J., Provost, P., Rådmark, O., Kim, S., et al. (2003) · Nature · doi:10.1038/nature01957 · Cited by 5,114
Evolution and Functions of Long Noncoding RNAs
Ponting, C. P., Oliver, P. L., & Reik, W. (2009) · Cell · doi:10.1016/j.cell.2009.02.006 · Cited by 4,208
Silencing of microRNAs in vivo with ‘antagomirs’
Krützfeldt, J., Rajewsky, N., Braich, R., Rajeev, K. G., Tuschl, T., Manoharan, M., & Stoffel, M. (2005) · Nature · doi:10.1038/nature04303 · Cited by 3,949
MicroRNA Targeting Specificity in Mammals: Determinants beyond Seed Pairing
Grimson, A., Farh, K. K.-H., Johnston, W. K., Garrett-Engele, P., Lim, L. P., & Bartel, D. P. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.06.017 · Cited by 3,766
A Long Noncoding RNA Controls Muscle Differentiation by Functioning as a Competing Endogenous RNA
Cesana, M., Cacchiarelli, D., Legnini, I., Santini, T., Sthandier, O., Chinappi, M., Tramontano, A., & Bozzoni, I. (2011) · Cell · doi:10.1016/j.cell.2011.09.028 · Cited by 2,554
Principles of MicroRNA–Target Recognition
Brennecke, J., Stark, A., Russell, R. B., & Cohen, S. M. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030085 · Cited by 2,378
Tripathi, V., Ellis, J. D., Shen, Z., Song, D. Y., Pan, Q., Watt, A. T., Freier, S. M., Bennett, C. F., Sharma, A., Bubulya, P. A., et al. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.08.011 · Cited by 2,219
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
MicroRNA-133 controls cardiac hypertrophy
Carè, A., Catalucci, D., Felicetti, F., Bonci, D., Addario, A., Gallo, P., Bang, M.-L., Segnalini, P., Gu, Y., Dalton, N. D., et al. (2007) · Nature Medicine · doi:10.1038/nm1582 · Cited by 1,776
Cited by
Analyzing MiRNA–LncRNA Interactions
Paraskevopoulou, M. D., & Hatzigeorgiou, A. G. (2016) · Methods in Molecular Biology · doi:10.1007/978-1-4939-3378-5_21 · Cited by 895
Tham, Y. K., Bernardo, B. C., Ooi, J. Y. Y., Weeks, K. L., & McMullen, J. R. (2015) · Archives of Toxicology · doi:10.1007/s00204-015-1477-x · Cited by 708
The novel regulatory role of lnc RNA‐mi RNA‐mRNA axis in cardiovascular diseases
Huang, Y. (2018) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.13866 · Cited by 445
Long noncoding RNA Chast promotes cardiac remodeling
Viereck, J., Kumarswamy, R., Foinquinos, A., Xiao, K., Avramopoulos, P., Kunz, M., Dittrich, M., Maetzig, T., Zimmer, K., Remke, J., et al. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf1475 · Cited by 370
RNA-based diagnostic and therapeutic strategies for cardiovascular disease
Lu, D., & Thum, T. (2019) · Nature Reviews Cardiology · doi:10.1038/s41569-019-0218-x · Cited by 331
Metadata
- Authors
- Wang, K., Liu, F., Zhou, L.-Y., Long, B., Yuan, S.-M., Wang, Y., Liu, C.-Y., Sun, T., Zhang, X.-J., & Li, P.-F.
- Venue
- Circulation Research
- Published
- 2014-04-25
- Volume
- 114
- Issue
- 9
- Pages
- 1377-1388
- ISSN
- 0009-7330 (ISSN-L)
- 1524-4571
- OpenAlex
- W2152894234
- Cited by
- 579
- References
- 45
- FWCI
- 36.64
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Long Noncoding RNA CHRF Regulates Cardiac Hypertrophy by Targeting miR-489. https://app.cochat.ai/papers/10.1161/circresaha.114.302476
- The paper
- Wang, K., Liu, F., Zhou, L.-Y., Long, B., Yuan, S.-M., Wang, Y., Liu, C.-Y., Sun, T., Zhang, X.-J., & Li, P.-F. (2014). The Long Noncoding RNA CHRF Regulates Cardiac Hypertrophy by Targeting miR-489. Circulation Research. https://doi.org/10.1161/circresaha.114.302476
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
