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Prediction of coronary disease incidence by biomarkers of inflammation, oxidation, and metabolism

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dc.contributor.author Subirana Cachinero, Isaac
dc.contributor.author Fitó Colomer, Montserrat
dc.contributor.author Díaz Gil, Oscar
dc.contributor.author Vila, Joan
dc.contributor.author Francés, Albert
dc.contributor.author Delpon, Eva
dc.contributor.author Sanchís, Juan
dc.contributor.author Elosua Llanos, Roberto
dc.contributor.author Muñoz-Aguayo, D.
dc.contributor.author Dégano, Irene R.
dc.contributor.author Marrugat de la Iglesia, Jaume
dc.date.accessioned 2019-02-01T09:13:30Z
dc.date.available 2019-02-01T09:13:30Z
dc.date.issued 2019
dc.identifier.citation Subirana I, Fitó M, Diaz O, Vila J, Francés A, Delpon E. et al. Prediction of coronary disease incidence by biomarkers of inflammation, oxidation, and metabolism. Sci Rep. 2018 Feb 16;8(1):3191. DOI: 10.1038/s41598-018-21482-y
dc.identifier.issn 2045-2322
dc.identifier.uri http://hdl.handle.net/10230/36472
dc.description.abstract The effect of circulating biomarkers in predicting coronary artery disease (CAD) is not fully elucidated. This study aimed to determine the relationship with CAD and the predictive capacity of nine biomarkers of inflammation (TNF-α, IL-10, IL-6, MCP-1, CRP), oxidation (GHS-Px), and metabolism (adiponectin, leptin, and insulin). This was a case-cohort study, within the REGICOR population-cohorts (North-Eastern Spain), of 105 CAD cases and 638 individuals randomly selected from a cohort of 5,404 participants aged 35-74 years (mean follow-up = 6.1 years). Biomarkers' hazard ratio (HR)/standard deviation was estimated with Cox models adjusted for age, sex, and classical risk factors. Discrimination improvement and reclassification were analyzed with the c-index and the Net reclassification index (NRI). GHS-Px (adjusted HRs = 0.77; 95%CI:0.60-0.99), insulin (1.46; 1.08-1.98), leptin (1.40; 1.03-1.90), IL-6 (1.34; 1.03-1.74), and TNF-α (1.80; 1.26-2.57) were significantly associated with CAD incidence. In the model adjusted for all biomarkers, TNF-α (1.87;1.31-2.66) and insulin (1.59;1.16-2.19) were independently associated with CAD. This final model, compared to a model without biomarkers, showed a c-index difference of 1.3% (-0.7, 3.2) and a continuous NRI of 33.7% (2.6, 61.9). TNF-α and insulin are independently associated with CAD incidence and they improve reclassification when added to a model including classical risk factors.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Nature Research
dc.relation.ispartof Scientific Reports. 2018 Feb 16;8(1):3191
dc.rights This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject.other Marcadors bioquímics
dc.subject.other Malalties coronàries
dc.title Prediction of coronary disease incidence by biomarkers of inflammation, oxidation, and metabolism
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/0.1038/s41598-018-21482-y
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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