Circulating miRNAs as Predictive Biomarkers of Type 2 Diabetes Mellitus Development in Coronary Heart Disease Patients from the CORDIOPREV Study.

dc.contributor.authorJiménez-Lucena, Rosa
dc.contributor.authorRangel-Zúñiga, Oriol Alberto
dc.contributor.authorAlcalá-Díaz, Juan Francisco
dc.contributor.authorLópez-Moreno, Javier
dc.contributor.authorRoncero-Ramos, Irene
dc.contributor.authorMolina-Abril, Helena
dc.contributor.authorYubero-Serrano, Elena Maria
dc.contributor.authorCaballero-Villarraso, Javier
dc.contributor.authorDelgado-Lista, Javier
dc.contributor.authorCastaño, Justo Pastor
dc.contributor.authorOrdovás, Jose Maria
dc.contributor.authorPérez-Martinez, Pablo
dc.contributor.authorCamargo, Antonio
dc.contributor.authorLópez-Miranda, José
dc.date.accessioned2025-01-07T13:43:14Z
dc.date.available2025-01-07T13:43:14Z
dc.date.issued2018-05-08
dc.description.abstractCirculating microRNAs (miRNAs) have been proposed as type 2 diabetes biomarkers, and they may be a more sensitive way to predict development of the disease than the currently used tools. Our aim was to identify whether circulating miRNAs, added to clinical and biochemical markers, yielded better potential for predicting type 2 diabetes. The study included 462 non-diabetic patients at baseline in the CORDIOPREV study. After a median follow-up of 60 months, 107 of them developed type 2 diabetes. Plasma levels of 24 miRNAs were measured at baseline by qRT-PCR, and other strong biomarkers to predict diabetes were determined. The ROC analysis identified 9 miRNAs, which, added to HbA1c, have a greater predictive value in early diagnosis of type 2 diabetes (AUC = 0.8342) than HbA1c alone (AUC = 0.6950). The miRNA and HbA1c-based model did not improve when the FINDRISC was included (AUC = 0.8293). Cox regression analyses showed that patients with low miR-103, miR-28-3p, miR-29a, and miR-9 and high miR-30a-5p and miR-150 circulating levels have a higher risk of disease (HR = 11.27; 95% CI = 2.61-48.65). Our results suggest that circulating miRNAs could potentially be used as a new tool for predicting the development of type 2 diabetes in clinical practice.
dc.identifier.doi10.1016/j.omtn.2018.05.002
dc.identifier.issn2162-2531
dc.identifier.pmcPMC6023857
dc.identifier.pmid30195754
dc.identifier.pubmedURLhttps://pmc.ncbi.nlm.nih.gov/articles/PMC6023857/pdf
dc.identifier.unpaywallURLhttp://www.cell.com/article/S2162253118300994/pdf
dc.identifier.urihttps://hdl.handle.net/10668/25788
dc.journal.titleMolecular therapy. Nucleic acids
dc.journal.titleabbreviationMol Ther Nucleic Acids
dc.language.isoen
dc.organizationSAS - Hospital Universitario Reina Sofía
dc.organizationSAS - Hospital Universitario Reina Sofía
dc.organizationInstituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC)
dc.page.number146-157
dc.pubmedtypeJournal Article
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectbiomarkers
dc.subjectmiRNAs
dc.subjectpredictive models
dc.subjecttype 2 diabetes mellitus
dc.titleCirculating miRNAs as Predictive Biomarkers of Type 2 Diabetes Mellitus Development in Coronary Heart Disease Patients from the CORDIOPREV Study.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number12

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