Heart failure (HF) remains a main cause of mortality worldwide. Risk stratification of patients with systolic chronic HF is critical to identify those who may benefit from advanced HF therapies. The aim of this study is to identify plasmatic proteins that could predict the early death (within 3 years) of HF patients with reduced ejection fraction hospitalized in CHRU de Lille. The subproteome targeted by an aptamer-based technology, the Slow Off-rate Modified Aptamer (SOMA) scan assay of 1310 proteins, was profiled in blood samples from 168 HF patients, and 203 proteins were significantly modulated between patients who died of cardiovascular death and patients who were alive after 3 years of HF evaluation (Wilcoxon test, FDR 5%). A molecular network was built using these 203 proteins, and the resulting network contained 2281 molecules assigned to 34 clusters annotated to biological pathways by Gene Ontology. This network model highlighted extracellular matrix organization as the main mechanism involved in early death in HF patients. In parallel, an adaptive Least Absolute Shrinkage and Selection Operator (LASSO) was performed on these 203 proteins, and six proteins were selected as candidates to predict early death in HF patients: complement C3, cathepsin S and F107B were decreased and MAPK5, MMP1 and MMP7 increased in patients who died of cardiovascular causes compared with patients living 3 years after HF evaluation. This proteomic signature of 6 circulating plasma proteins allows the identification of systolic HF patients with a risk of early death.

Heart failure (HF) remains a main cause of mortality worldwide. Risk stratification of patients with systolic chronic HF is critical to identify those who may benefit from advanced HF therapies. The aim of this study is to identify plasmatic proteins that could predict the early death (within 3 years) of HF patients with reduced ejection fraction hospitalized in cHRU de Lille. the subproteome targeted by an aptamer-based technology, the Slow Off-rate Modified Aptamer (SOMA) scan assay of 1310 proteins, was profiled in blood samples from 168 HF patients, and 203 proteins were significantly modulated between patients who died of cardiovascular death and patients who were alive after 3 years of HF evaluation (Wilcoxon test, FDR 5%). A molecular network was built using these 203 proteins, and the resulting network contained 2281 molecules assigned to 34 clusters annotated to biological pathways by Gene Ontology. This network model highlighted extracellular matrix organization as the main mechanism involved in early death in HF patients. In parallel, an adaptive Least Absolute Shrinkage and Selection Operator (LASSO) was performed on these 203 proteins, and six proteins were selected as candidates to predict early death in HF patients: complement C3, cathepsin S and F107B were decreased and MAPK5, MMP1 and MMP7 increased in patients who died of cardiovascular causes compared with patients living 3 years after HF evaluation. This proteomic signature of 6 circulating plasma proteins allows the identification of systolic HF patients with a risk of early death. Heart failure (HF) is an important cause of mortality worldwide 1. HF has different origins: non-ischaemic, such as cardiomyopathies, or ischaemic, after myocardial infarction (MI). Detection and treatment of HF are still unsatisfactory. Risk stratification of systolic HF patients is an important issue that can lead high-risk patients to invasive strategies New York Heart Association (NYHA) class, left ventricular ejection fraction (LVEF), B-type natriuretic peptide (BNP) level and peak exercise oxygen consumption (peak VO 2) have been associated with the early death of HF patients 2,3. However, this stratification needs to be improved. Prediction of mortality in HF patients using "conventional" prognostic evaluation showed moderate success and emphasized the requirement of models using a systems biology approach 4. We previously performed proteomic profiling in a case/control study that had included patients with systolic HF. Forty-two differentially intense peaks were identified and used to develop proteomic scores. These scores allowed a better discrimination of HF patients 5. Recently, a profiling by matrix-assisted laser desorption-ionization MS (MALDI-MS) showed that 14 peptides identified in plasma can predict clinical outcomes in HF patients 6. Recent advances in systems biology have opened new opportunities in the study of biomarker discovery and of the mechanistic context of HF. While previous analyses relied on the study of individual molecules, molecula...