The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Plasma MicroRNA Profiling Reveals Loss of Endothelial MiR-126 and Other MicroRNAs in Type 2 Diabetes
Abstract
Rationale: MicroRNAs (miRNAs) have been implicated in the epigenetic regulation of key metabolic, inflammatory, and antiangiogenic pathways in type 2 diabetes (DM) and may contribute to common disease complications. Objective: In this study, we explore plasma miRNA profiles in patients with DM. Methods and Results: Total RNA was extracted from plasma samples of the prospective population-based Bruneck study. A total of 13 candidate miRNAs identified by microarray screening and miRNA network inference were quantified by quantitative PCR in all diabetic patients of the Bruneck study and age- and sex-matched controls (1995 evaluation, n=80 each). Quantitative PCR assessment revealed lower plasma levels of miR-20b, miR-21, miR-24, miR-15a, miR-126, miR-191, miR-197, miR-223, miR-320, and miR-486 in prevalent DM, but a modest increase of miR-28-3p. Findings emerged as robust in multivariable analysis and were independent of the standardization procedure applied. For endothelial miR-126, results were confirmed in the entire Bruneck cohort (n=822) in univariate (odds ratio [95% confidence interval], 0.38 [0.26 to 0.55]; P =2.72×10 −7 ) and multivariate analyses (0.57 [0.37 to 0.86]; P =0.0082). Importantly, reduced miR-15a, miR-29b, miR-126, miR-223, and elevated miR-28-3p levels antedated the manifestation of disease. Most differences in miRNA levels were replicated in plasma obtained from hyperglycemic Lep ob mice. High glucose concentrations reduced the miR-126 content of endothelial apoptotic bodies. Similarly in patients with DM, the reduction of miR-126 was confined to circulating vesicles in plasma. Conclusions: We reveal a plasma miRNA signature for DM that includes loss of endothelial miR-126. These findings might explain the impaired peripheral angiogenic signaling in patients with DM.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“High glucose conditions decrease miR-126 content in EC derived microparticles36 and circulating vesicles in plasma5.”
From MiR-126 Mediates Brain Endothelial Cell Exosome Treatment–Induced Neurorestorative Effects After Stroke in Type 2 Diabetes Mellitus Mice (2019) · cites this paper as [5]
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
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
Hosmer, D. W., & Lemeshow, S. (2000) · doi:10.1002/0471722146 · Cited by 20,302
Circulating microRNAs, potential biomarkers for drug-induced liver injury
Wang, K., Zhang, S., Marzolf, B., Troisch, P., Brightman, A., Hu, Z., Hood, L. E., & Galas, D. J. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0813371106 · Cited by 1,149
Research works printed but not linked: 37
- 10.1016/j.cell.2009.01.002 · DOI · Paper page
- 10.1016/j.tcb.2006.12.007 · DOI
- 10.1016/j.devcel.2006.09.009 · DOI · Paper page
- 10.1161/CIRCRESAHA.107.163147 · DOI
- 10.1161/circresaha.108.183426 · DOI
- 10.1161/01.RES.0000265065.26744.17 · DOI
- 10.1161/CIRCRESAHA.107.153916 · DOI
- 10.1073/pnas.0804549105 · DOI · Paper page
- 10.1371/journal.pone.0005532 · DOI
- 10.1373/clinchem.2009.131797 · DOI
- 10.1093/eurheartj/ehq013 · DOI
- 10.1373/clinchem.2009.125310 · DOI
- 10.1161/CIRCRESAHA.109.215566 · DOI
- 10.1161/circresaha.110.218297 · DOI
- 10.1056/NEJM199306103282306 · DOI
- 10.1161/circulationaha.108.792986 · DOI
- 10.1056/NEJMoa012673 · DOI
- 10.2337/diabetes.53.7.1782 · DOI
- 10.1161/circulationaha.106.686774 · DOI
- 10.1016/S0304-3940(02)01423-4 · DOI
- 10.1016/S0167-2789(97)00117-6 · DOI
- 10.1073/pnas.0507432102 · DOI
- 10.1371/journal.pbio.0050008 · DOI · Paper page
- 10.1038/msb4100120 · DOI
- 10.1126/science.1173299 · DOI
- 10.1038/msb4100180 · DOI · Paper page
- 10.1002/pmic.200900065 · DOI
- 10.1161/circresaha.108.182261 · DOI
- 10.1182/blood-2009-02-205930 · DOI
- 10.1158/0008-5472.CAN-08-4277 · DOI
- 10.1073/pnas.0506654102 · DOI
- 10.1016/j.devcel.2008.07.008 · DOI · Paper page
- 10.1016/j.devcel.2008.07.002 · DOI · Paper page
- 10.1016/S0008-6363(03)00367-5 · DOI
- 10.1126/scisignal.2000610 · DOI
- 10.1161/01.CIR.102.2.185 · DOI
- 10.1074/mcp.R600007-MCP200 · DOI
Cited by
Sorted by citations
Ying, W., Riopel, M., Bandyopadhyay, G., Dong, Y., Birmingham, A., Seo, J. B., Ofrecio, J. M., Wollam, J., Hernandez-Carretero, A., Fu, W., et al. (2017) · Cell · doi:10.1016/j.cell.2017.08.035 · Cited by 1,191
Circulating microRNAs as novel biomarkers for diabetes mellitus
Guay, C., & Regazzi, R. (2013) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2013.86 · Cited by 563
Type-2 diabetes mellitus and cardiovascular disease
Henning, R. J. (2018) · Future Cardiology · doi:10.2217/fca-2018-0045 · Cited by 398
Type 2 diabetes mellitus and cardiovascular disease: Genetic and epigenetic links
De Rosa, S., Arcidiacono, B., Chiefari, E., Brunetti, A., Indolfi, C., & Foti, D. P. (2018) · Frontiers in Endocrinology · doi:10.3389/fendo.2018.00002 · Cited by 369
Scioli, M. G., Storti, G., D’Amico, F., Rodríguez Guzmán, R., Centofanti, F., Doldo, E., Céspedes Miranda, E. M., & Orlandi, A. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9061995 · Cited by 281
Metadata
- Authors
- Zampetaki, A., Kiechl, S., Drozdov, I., Willeit, P., Mayr, U., Prokopi, M., Mayr, A., Weger, S., Oberhollenzer, F., Bonora, E., Shah, A., Willeit, J., & Mayr, M.
- Affiliations
- From the King's College London British Heart Foundation Centre (A.Z., I.D., U.M., M.P., A.S., M.M.) and Centre for Bioinformatics-School of Physical Sciences and Engineering (I.D.), King's College London, United Kingdom; Department of Neurology (S.K., P.W., J.W.), Medical University Innsbruck, Austria; Department of Public Health and Primary Care (P.W.), University of Cambridge, United Kingdom; Department of Laboratory Medicine and Department of Internal Medicine (A.M., S.W., F.O.), Bruneck Hospital...
- Venue
- Circulation Research
- Published
- 2010-09-17
- Volume
- 107
- Issue
- 6
- Pages
- 810-817
- ISSN
- 0009-7330
- 1524-4571
- Cited by
- 1,283
- References
- 3
- Language
- en
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