The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.
miRNAS in cardiovascular diseases: potential biomarkers, therapeutic targets and challenges
Open accessAbstract
Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality in the world. Although considerable progress has been made in the diagnosis, treatment and prognosis of CVD, there is still a critical need for novel diagnostic biomarkers and new therapeutic interventions to decrease the incidence of this disease. Recently, there is increasing evidence that circulating miRNAs (miRNAs), i.e. endogenous, stable, single-stranded, short, non-coding RNAs, can be used as diagnostic biomarkers for CVD. Furthermore, miRNAs represent potential novel therapeutic targets for several cardiovascular disorders. In this review we provides an overview of the effects of several CVD; including heart failure, acute myocardial infarction, arrhythmias and pulmonary hypertension; on levels of circulating miRNAs. In addition, the use of miRNA as therapeutic targets is also discussed, as well as challenges and recommendations in their use in the diagnosis of CVD.
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
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
The 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
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005) · Cell · doi:10.1016/j.cell.2004.12.035 · Cited by 11,855
Prediction of Mammalian MicroRNA Targets
Lewis, B. P., Shih, I.-H., Jones-Rhoades, M. W., Bartel, D. P., & Burge, C. B. (2003) · Cell · doi:10.1016/s0092-8674(03)01018-3 · Cited by 5,199
Chen, X., Ba, Y., Ma, L., Cai, X., Yin, Y., Wang, K., Guo, J., Zhang, Y., Chen, J., Guo, X., et al. (2008) · Cell Research · doi:10.1038/cr.2008.282 · Cited by 4,560
Self-citationWightman, B., Ha, I., & Ruvkun, G. (1993) · Cell · doi:10.1016/0092-8674(93)90530-4 · Cited by 4,292
The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation
Chen, J.-F., Mandel, E. M., Thomson, J. M., Wu, Q., Callis, T. E., Hammond, S. M., Conlon, F. L., & Wang, D.-Z. (2006) · Nature Genetics · doi:10.1038/ng1725 · Cited by 2,779
MicroRNA-21 contributes to myocardial disease by stimulating MAP kinase signalling in fibroblasts
Thum, T., Gross, C., Fiedler, J., Fischer, T., Kissler, S., Bussen, M., Galuppo, P., Just, S., Rottbauer, W., Frantz, S., et al. (2008) · Nature · doi:10.1038/nature07511 · Cited by 2,349
Secretory Mechanisms and Intercellular Transfer of MicroRNAs in Living Cells
Kosaka, N., Iguchi, H., Yoshioka, Y., Takeshita, F., Matsuki, Y., & Ochiya, T. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m110.107821 · Cited by 1,934
Dysregulation of microRNAs after myocardial infarction reveals a role of miR-29 in cardiac fibrosis
van Rooij, E., Sutherland, L. B., Thatcher, J. E., DiMaio, J. M., Naseem, R. H., Marshall, W. S., Hill, J. A., & Olson, E. N. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0805038105 · Cited by 1,844
Cited by
Biomarkers for the diagnosis and management of heart failure
Castiglione, V., Aimo, A., Vergaro, G., Saccaro, L., Passino, C., & Emdin, M. (2022) · Heart Failure Reviews · doi:10.1007/s10741-021-10105-w · Cited by 512
Griñán-Ferré, C., Bellver-Sanchis, A., Izquierdo, V., Corpas, R., Roig-Soriano, J., Chillón, M., Andres-Lacueva, C., Somogyvári, M., Sőti, C., Sanfeliu, C., et al. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101271 · Cited by 208
Cardiovascular Risk and Resilience Among Black Adults: Rationale and Design of the MECA Study
Islam, S. J., Kim, J. H., Topel, M., Liu, C., Ko, Y., Mujahid, M. S., Sims, M., Mubasher, M., Ejaz, K., Morgan‐Billingslea, J., et al. (2020) · Journal of the American Heart Association · doi:10.1161/jaha.119.015247 · Cited by 23
Kalpachidou, T., Kummer, K. K., Mitrić, M., & Kress, M. (2019) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2019.00283 · Cited by 10
Metadata
- Authors
- Zhou, S.-S., Jin, J.-P., Wang, J.-Q., Zhang, Z.-G., Freedman, J. H., Zheng, Y., & Cai, L.
- Venue
- Acta Pharmacologica Sinica
- Published
- 2018-06-07
- Volume
- 39
- Issue
- 7
- Pages
- 1073-1084
- ISSN
- 0253-9756 (ISSN-L)
- 1671-4083
- 1745-7254
- OpenAlex
- W2807343509
- Cited by
- 675
- References
- 112
- FWCI
- 13.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: miRNAS in cardiovascular diseases: potential biomarkers, therapeutic targets and challenges. https://app.cochat.ai/papers/10.1038/aps.2018.30
- The paper
- Zhou, S.-S., Jin, J.-P., Wang, J.-Q., Zhang, Z.-G., Freedman, J. H., Zheng, Y., & Cai, L. (2018). miRNAS in cardiovascular diseases: potential biomarkers, therapeutic targets and challenges. Acta Pharmacologica Sinica. https://doi.org/10.1038/aps.2018.30
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.