Multimarker proteomic profiling for the prediction of cardiovascular mortality in patients with chronic heart failure.

Philippe Rouet,Gilles Lemesle,Fleur Maury,Olivia Beseme,Christophe Bauters,Philippe Amouyel,Lionel Ovart,Nicolas Lamblin,Pascal De Groote,Florence Pinet

doi:10.1371/journal.pone.0119265

Abstract

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.

Highlights

In spite of recent therapeutic improvements, chronic heart failure (HF) remains a major public health problem [1,2] with a high rate of mortality [3]
Variables such as NewYork Heart Association (NYHA) class, left ventricular ejection fraction (LVEF), brain natriuretic peptide (BNP), or variables obtained during cardiopulmonary exercise testing (peak oxygen consumption) have been associated with the outcome of HF patients [4,5,6,7]
The 42 ion m/z peaks found to be differentially intense after Bonferroni correction were used to build the proteomic scores

Summary

Introduction

In spite of recent therapeutic improvements, chronic heart failure (HF) remains a major public health problem [1,2] with a high rate of mortality [3]. Proteomic Profiling for Risk Prediction in Chronic Heart Failure patients with systolic HF since high-risk patients can be considered for invasive strategies such as implantable assist devices and/or cardiac transplantation Variables such as NewYork Heart Association (NYHA) class, left ventricular ejection fraction (LVEF), brain natriuretic peptide (BNP), or variables obtained during cardiopulmonary exercise testing (peak oxygen consumption (peak VO2)) have been associated with the outcome of HF patients [4,5,6,7]. In spite of these advances, risk stratification of HF patients needs to be further improved. There remains variability in the prognosis with some patients who are categorized at low risk but experience early mortality; and patients categorized as severe but have an unexpectedly prolonged survival

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