The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Five Freely Circulating miRNAs and Bone Tissue miRNAs Are Associated With Osteoporotic Fractures
Open accessAbstract
Osteoporosis as a systemic skeletal disorder is characterized by increased bone fragility and the risk of fractures. According to the World Health Organization, osteoporosis is one of the 10 most common diseases and affects approximately 75 million people in Europe, the United States, and Japan. In this context, the identification of specific microRNA (miRNA) signatures is an important step for new diagnostic and therapeutic approaches. The focus of interest on miRNAs as biomarkers came with new publications identifying free circulating extracellular miRNAs associated with various types of cancer. This study aimed to identify specific miRNAs in patients with osteoporotic fractures compared with nonosteoporotic fractures. For the array analysis, miRNAs were isolated from the serum of 20 patients with hip fractures, transcribed, and the samples were pooled into 10 osteoporotic and 10 nonosteoporotic specimens. With each pool of samples, human serum and plasma miRNA PCR arrays were performed, which are able to identify 83 different miRNAs. Subsequently, a separate validation analysis of each miRNA found to be regulated in the array followed with miRNA samples isolated from the serum of 30 osteoporotic and 30 nonosteoporotic patients and miRNA samples isolated from the bone tissue of 20 osteoporotic and 20 nonosteoporotic patients. With the validation analysis of the regulated miRNAs, we identified 9 miRNAs, namely miR-21, miR-23a, miR-24, miR-93, miR-100, miR-122a, miR-124a, miR-125b, and miR-148a, that were significantly upregulated in the serum of patients with osteoporosis. In the bone tissue of osteoporotic patients, we identified that miR-21, miR-23a, miR-24, miR-25, miR-100, and miR-125b displayed a significantly higher expression. A total of 5 miRNAs display an upregulation both in serum and bone tissue. This study reveals an important role for several miRNAs in osteoporotic patients and suggested that they may be used as biomarkers for diagnostic purposes and may be a target for treating bone loss and optimizing fracture healing in osteoporotic patients. © 2014 American Society for Bone and Mineral Research.
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
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments
Bustin, S. A., Benes, V., Garson, J. A., Hellemans, J., Huggett, J., Kubista, M., Mueller, R., Nolan, T., Pfaffl, M. W., Shipley, G. L., et al. (2009) · Clinical Chemistry · doi:10.1373/clinchem.2008.112797 · Cited by 16,303
MicroRNAs: small RNAs with a big role in gene regulation
He, L., & Hannon, G. J. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1379 · Cited by 7,118
Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., et al. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.242606799 · Cited by 5,111
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
Pathogenesis of osteoporosis: concepts, conflicts, and prospects
Raisz, L. G. (2005) · Journal of Clinical Investigation · doi:10.1172/jci27071 · Cited by 1,779 · cited 2×
“Skeletal fragility arises from inefficacy to produce the optimal bone mass, excessive bone resorption, and inadequate formation response during bone remodeling.((1)) An increasing number of studies indicate that osteoporosis is caused by extensive interactions among local and systemic regulators of bone cell function.”
BackgroundGarzon, R., Calin, G. A., & Croce, C. M. (2009) · Annual Review of Medicine · doi:10.1146/annurev.med.59.053006.104707 · Cited by 1,770
Schuit, S. C. E., van der Klift, M., Weel, A. E. A. M., de Laet, C. E. D. H., Burger, H., Seeman, E., Hofman, A., Uitterlinden, A. G., van Leeuwen, J. P. T. M., & Pols, H. A. P. (2004) · Bone · doi:10.1016/j.bone.2003.10.001 · Cited by 1,651
Sempere, L. F., Freemantle, S., Pitha-Rowe, I., Moss, E., Dmitrovsky, E., & Ambros, V. (2004) · Genome Biology · doi:10.1186/gb-2004-5-3-r13 · Cited by 1,578
Cited by
miR-21 deficiency inhibits osteoclast function and prevents bone loss in mice
Hu, C.-H., Sui, B.-D., Du, F.-Y., Shuai, Y., Zheng, C.-X., Zhao, P., Yu, X.-R., & Jin, Y. (2017) · Scientific Reports · doi:10.1038/srep43191 · Cited by 127
New Insights into Monogenic Causes of Osteoporosis
Mäkitie, R. E., Costantini, A., Kämpe, A., Alm, J. J., & Mäkitie, O. (2019) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00070 · Cited by 108
Yavropoulou, M. P., Anastasilakis, A. D., Makras, P., Tsalikakis, D. G., Grammatiki, M., & Yovos, J. G. (2017) · European Journal of Endocrinology · doi:10.1530/eje-16-0583 · Cited by 102
MicroRNA-23a-3p inhibitor decreases osteonecrosis incidence in a rat model
Dong, Y., Li, T., Li, Y., Ren, S., Fan, J., & Weng, X. (2017) · Molecular Medicine Reports · doi:10.3892/mmr.2017.7808 · Cited by 17
The Ambivalent Role of miRNA-21 in Trauma and Acute Organ Injury
Ritter, A., Han, J., Bianconi, S., Henrich, D., Marzi, I., Leppik, L., & Weber, B. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252011282 · Cited by 6
Metadata
- Authors
- Seeliger, C., Karpinski, K., Haug, A. T., Vester, H., Schmitt, A., Bauer, J. S., & van Griensven, M.
- Venue
- Journal of Bone and Mineral Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-01-16
- Volume
- 29
- Issue
- 8
- Pages
- 1718-1728
- ISSN
- 0884-0431 (ISSN-L)
- 1523-4681
- OpenAlex
- W2056971814
- Cited by
- 329
- References
- 42
- FWCI
- 9.14
- Type
- journal article
- Language
- en
- Open access
- green
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: Five Freely Circulating miRNAs and Bone Tissue miRNAs Are Associated With Osteoporotic Fractures. https://app.cochat.ai/papers/10.1002/jbmr.2175
- The paper
- Seeliger, C., Karpinski, K., Haug, A. T., Vester, H., Schmitt, A., Bauer, J. S., & van Griensven, M. (2014). Five Freely Circulating miRNAs and Bone Tissue miRNAs Are Associated With Osteoporotic Fractures. Journal of Bone and Mineral Research. https://doi.org/10.1002/jbmr.2175
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.
