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dc.contributor.authorHtun, NM
dc.contributor.authorMagliano, DJ
dc.contributor.authorZhang, Z-Y
dc.contributor.authorLyons, J
dc.contributor.authorPetit, T
dc.contributor.authorNkuipou-Kenfack, E
dc.contributor.authorRamirez-Torres, A
dc.contributor.authorvon zur Muhlen, C
dc.contributor.authorMaahs, D
dc.contributor.authorSchanstra, JP
dc.contributor.authorPontillo, C
dc.contributor.authorPejchinovski, M
dc.contributor.authorSnell-Bergeon, JK
dc.contributor.authorDelles, C
dc.contributor.authorMischak, H
dc.contributor.authorStaessen, JA
dc.contributor.authorShaw, JE
dc.contributor.authorKoeck, T
dc.contributor.authorPeter, K
dc.date.accessioned2020-12-22T05:25:24Z
dc.date.available2020-12-22T05:25:24Z
dc.date.issued2017-03-08
dc.identifierpii: PONE-D-16-45061
dc.identifier.citationHtun, N. M., Magliano, D. J., Zhang, Z. -Y., Lyons, J., Petit, T., Nkuipou-Kenfack, E., Ramirez-Torres, A., von zur Muhlen, C., Maahs, D., Schanstra, J. P., Pontillo, C., Pejchinovski, M., Snell-Bergeon, J. K., Delles, C., Mischak, H., Staessen, J. A., Shaw, J. E., Koeck, T. & Peter, K. (2017). Prediction of acute coronary syndromes by urinary proteome analysis. PLOS ONE, 12 (3), https://doi.org/10.1371/journal.pone.0172036.
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/11343/258284
dc.description.abstractIdentification of individuals who are at risk of suffering from acute coronary syndromes (ACS) may allow to introduce preventative measures. We aimed to identify ACS-related urinary peptides, that combined as a pattern can be used as prognostic biomarker. Proteomic data of 252 individuals enrolled in four prospective studies from Australia, Europe and North America were analyzed. 126 of these had suffered from ACS within a period of up to 5 years post urine sampling (cases). Proteomic analysis of 84 cases and 84 matched controls resulted in the discovery of 75 ACS-related urinary peptides. Combining these to a peptide pattern, we established a prognostic biomarker named Acute Coronary Syndrome Predictor 75 (ACSP75). ACSP75 demonstrated reasonable prognostic discrimination (c-statistic = 0.664), which was similar to Framingham risk scoring (c-statistics = 0.644) in a validation cohort of 42 cases and 42 controls. However, generating by a composite algorithm named Acute Coronary Syndrome Composite Predictor (ACSCP), combining the biomarker pattern ACSP75 with the previously established urinary proteomic biomarker CAD238 characterizing coronary artery disease as the underlying aetiology, and age as a risk factor, further improved discrimination (c-statistic = 0.751) resulting in an added prognostic value over Framingham risk scoring expressed by an integrated discrimination improvement of 0.273 ± 0.048 (P < 0.0001) and net reclassification improvement of 0.405 ± 0.113 (P = 0.0007). In conclusion, we demonstrate that urinary peptide biomarkers have the potential to predict future ACS events in asymptomatic patients. Further large scale studies are warranted to determine the role of urinary biomarkers in clinical practice.
dc.languageEnglish
dc.publisherPUBLIC LIBRARY SCIENCE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titlePrediction of acute coronary syndromes by urinary proteome analysis
dc.typeJournal Article
dc.identifier.doi10.1371/journal.pone.0172036
melbourne.affiliation.departmentMelbourne School of Population and Global Health
melbourne.source.titlePLoS One
melbourne.source.volume12
melbourne.source.issue3
dc.rights.licenseCC BY
melbourne.elementsid1190477
melbourne.contributor.authorLyons, Jasmine
melbourne.contributor.authorMagliano, Dianna
melbourne.contributor.authorPeter, Karlheinz
dc.identifier.eissn1932-6203
melbourne.accessrightsOpen Access


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