Risk stratification of patients with systolic chronic heart failure (HF) is critical to better identify those who may benefit the most from invasive therapeutic strategies such as cardiac transplantation. In spite of recent advances, risk stratification of HF patients needs to be further improved. Indeed, there remains variability in the prognosis with some patients who are categorized at low risk but experience early mortality; and conversely, patients categorized as severe but have an unexpectedly prolonged survival. Proteomics has been used to provide prognostic information in various diseases.Aim – Our aim was to investigate the potential value of plasma proteomic profiling for risk stratification in HF and to find new circulating biomarkers that are associated with early cardiovascular mortality of chronic HF patients.Methods and results – For that purpose, we first designed 2 populations: a discovery and a validation population. Both populations issued from the INsuffisance CArdiaque (INCA) cohort, which is constituted of all consecutive patients referred in our institution for extensive prognostic evaluation of systolic chronic HF (LVEF <45%) between November 1998 and May 2010. For the discovery phase (case/control population), we selected 198 patients included between November 1998 and December 2005: 99 patients who died from cardiovascular cause within 3 years after the initial evaluation (cases) were individually matched for age, sex, and HF etiology with 99 patients who were still alive at 3 years (controls). For the validation phase, we evaluated a cohort of 344 consecutive patients included between January 2006 and May 2010. Study populations were carefully phenotyped. Cardiovascular death included cardiovascular-related death, urgent transplantations defined as United Network for Organ Sharing status 1 and urgent assist device implantation. A proteomic profiling using surface enhanced laser desorption ionization - time of flight - mass spectrometry was then performed in the case/control discovery population on plasma samples collected at inclusion. Plasma samples were depleted for major proteins and randomly analyzed in duplicate using CM10 (Weak Cation Exchanger) and H50 (Reverse Phase) proteinchip arrays. Forty two ion m/z peaks were found differentially abundant between cases and controls in the discovery population and were used to develop proteomic scores predicting cardiovascular death using 3 statistical regression methods: support vector machine, sparse partial least square discriminant analysis and lasso logistic regression. The proteomic scores were then tested in the validation population and score levels were significantly higher in patients who subsequently died within 3 years with the 3 methods. Proteomic scores remained significantly associated with cardiovascular mortality after adjustment on confounders. Furthermore, 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 on top of “classic” prognostic evaluation. The next step was the purification and identification of the proteins related to the different m/z peaks (n=13) that were found significantly differentially abundant in both populations. We have currently identified several peaks as apolipoproteins: 14511 CM10-BM (ApoA1), 29024 CM10-BM (ApoA1), 3267 H50-BM (ApoC1), 6416 H50-BM (ApoC1), 6616 H50-BM (ApoC1), 6825 H50-BM (ApoC1), 8764 H50-BM (ApoC3), 9421 H50-BM (ApoC3). This has led to the quantification of these apolipoproteins in the INCA population using mass reaction monitoring technique.Conclusion – Proteomic analysis of plasma proteins may help to improve risk prediction of early mortality in HF patients.Perspectives – Further investigations are ongoing in order to determine the impact of the different apolipoproteins tested in risk stratification of chronic HF patients.