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Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure

Risk stratification of patients with systolic chronic heart failure (HF) is critical to better identify those who may benefit from invasive therapeutic strategies such as cardiac transplantation. Proteomics has been used to provide prognostic information in various diseases. Our aim was to investiga...

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Autores principales: Lemesle, Gilles, Maury, Fleur, Beseme, Olivia, Ovart, Lionel, Amouyel, Philippe, Lamblin, Nicolas, de Groote, Pascal, Bauters, Christophe, Pinet, Florence
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408082/
https://www.ncbi.nlm.nih.gov/pubmed/25905469
http://dx.doi.org/10.1371/journal.pone.0119265
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author Lemesle, Gilles
Maury, Fleur
Beseme, Olivia
Ovart, Lionel
Amouyel, Philippe
Lamblin, Nicolas
de Groote, Pascal
Bauters, Christophe
Pinet, Florence
author_facet Lemesle, Gilles
Maury, Fleur
Beseme, Olivia
Ovart, Lionel
Amouyel, Philippe
Lamblin, Nicolas
de Groote, Pascal
Bauters, Christophe
Pinet, Florence
author_sort Lemesle, Gilles
collection PubMed
description Risk stratification of patients with systolic chronic heart failure (HF) is critical to better identify those who may benefit from invasive therapeutic strategies such as cardiac transplantation. Proteomics has been used to provide prognostic information in various diseases. Our aim was to investigate the potential value of plasma proteomic profiling for risk stratification in HF. A proteomic profiling using surface enhanced laser desorption ionization - time of flight - mass spectrometry was performed in a case/control discovery population of 198 patients with systolic HF (left ventricular ejection fraction <45%): 99 patients who died from cardiovascular cause within 3 years and 99 patients alive at 3 years. Proteomic scores predicting cardiovascular death were developed using 3 regression methods: support vector machine, sparse partial least square discriminant analysis, and lasso logistic regression. Forty two ion m/z peaks were differentially intense between cases and controls in the discovery population and were used to develop proteomic scores. In the validation population, score levels were higher in patients who subsequently died within 3 years. Similar areas under the curves (0.66 – 0.68) were observed for the 3 methods. After adjustment on confounders, proteomic scores remained significantly associated with cardiovascular mortality. Use of the proteomic scores allowed a significant improvement in discrimination of HF patients as determined by integrated discrimination improvement and net reclassification improvement indexes. In conclusion, proteomic analysis of plasma proteins may help to improve risk prediction in HF patients.
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spelling pubmed-44080822015-05-04 Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure Lemesle, Gilles Maury, Fleur Beseme, Olivia Ovart, Lionel Amouyel, Philippe Lamblin, Nicolas de Groote, Pascal Bauters, Christophe Pinet, Florence PLoS One Research Article Risk stratification of patients with systolic chronic heart failure (HF) is critical to better identify those who may benefit from invasive therapeutic strategies such as cardiac transplantation. Proteomics has been used to provide prognostic information in various diseases. Our aim was to investigate the potential value of plasma proteomic profiling for risk stratification in HF. A proteomic profiling using surface enhanced laser desorption ionization - time of flight - mass spectrometry was performed in a case/control discovery population of 198 patients with systolic HF (left ventricular ejection fraction <45%): 99 patients who died from cardiovascular cause within 3 years and 99 patients alive at 3 years. Proteomic scores predicting cardiovascular death were developed using 3 regression methods: support vector machine, sparse partial least square discriminant analysis, and lasso logistic regression. Forty two ion m/z peaks were differentially intense between cases and controls in the discovery population and were used to develop proteomic scores. In the validation population, score levels were higher in patients who subsequently died within 3 years. Similar areas under the curves (0.66 – 0.68) were observed for the 3 methods. After adjustment on confounders, proteomic scores remained significantly associated with cardiovascular mortality. Use of the proteomic scores allowed a significant improvement in discrimination of HF patients as determined by integrated discrimination improvement and net reclassification improvement indexes. In conclusion, proteomic analysis of plasma proteins may help to improve risk prediction in HF patients. Public Library of Science 2015-04-23 /pmc/articles/PMC4408082/ /pubmed/25905469 http://dx.doi.org/10.1371/journal.pone.0119265 Text en © 2015 Lemesle et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lemesle, Gilles
Maury, Fleur
Beseme, Olivia
Ovart, Lionel
Amouyel, Philippe
Lamblin, Nicolas
de Groote, Pascal
Bauters, Christophe
Pinet, Florence
Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure
title Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure
title_full Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure
title_fullStr Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure
title_full_unstemmed Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure
title_short Multimarker Proteomic Profiling for the Prediction of Cardiovascular Mortality in Patients with Chronic Heart Failure
title_sort multimarker proteomic profiling for the prediction of cardiovascular mortality in patients with chronic heart failure
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408082/
https://www.ncbi.nlm.nih.gov/pubmed/25905469
http://dx.doi.org/10.1371/journal.pone.0119265
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