Abstract Background Though current heart failure (HF) biomarkers are highly prognostic, systematically characterizing associations between circulating proteins and risk of subsequent events may improve clinical risk prediction and illuminate new biological pathways. Large-scale assays measuring thousands of proteins now enable unbiased proteomic investigation in clinical trials. Purpose To identify and replicate serum proteins associated with HF events in patients with chronic HF with reduced ejection fraction (HFrEF), and to develop and validate a proteomic risk score. Methods Serum levels of 4076 proteins were measured at baseline in the ATMOSPHERE (n=1261, 487 events over 6 years) and PARADIGM-HF (n=1257, 287 events over 4 years) trials of chronic HFrEF using a modified aptamer-based proteomics assay. Proteins associated with the primary endpoint, HF hospitalization or cardiovascular death, were identified in the ATMOSPHERE discovery cohort (false discovery rate<0.05) by Cox regression adjusted for age, sex, treatment arm, and anticoagulant use, and replicated in PARADIGM-HF (Bonferroni-corrected p<0.05). A proteomic risk score was derived in ATMOSPHERE using Cox LASSO penalized regression and evaluated in PARADIGM-HF compared to the MAGGIC clinical risk score and N-terminal pro-B-type natriuretic peptide (NT-proBNP). For proteins associated with the primary endpoint, pathway analysis was conducted using Ingenuity Pathway analysis and an exploratory two-sample Mendelian randomization was performed using genetic and outcome data from both trials and protein quantitative trait loci from deCODE to infer which identified proteins contribute to HF prognosis. Results We identified 377 serum proteins associated with the primary endpoint in ATMOSPHERE and replicated 167 in PARADIGM-HF. Prognostic proteins included known HF biomarkers Growth Differentiation Factor 15, NT-proBNP, and Angiopoietin-2, and also a previously unrecognized HF biomarker: Sushi, Von Willebrand Factor Type A, EGF And Pentraxin Domain Containing 1 (SVEP1) (HR 1.60 [95% CI 1.44–1.79] per standard deviation [SD], p=2x10–17) (Table 1). Proteins related to hepatic fibrosis, granulocyte adhesion, and inhibition of matrix metalloproteinases were over-represented. A 64-protein risk score derived in ATMOSPHERE predicted clinical events in PARADIGM-HF with greater discrimination (c-statistic 0.70) than the MAGGIC clinical score (c-statistic 0.61), NT-proBNP (c-statistic 0.65), or both (c-statistic 0.66) (Figure 1). Genetically predicted levels of NT-proBNP, WISP2, FSTL1, and CTSS were associated with the primary endpoint by Mendelian randomization. Conclusions We identify SVEP1, an extracellular matrix protein known to cause inflammation in vascular smooth muscle cells, as a previously unrecognized HF biomarker. A 64-protein score improved risk discrimination compared with NT-proBNP and may assist in identifying high-risk patients for clinical trials or disease management programs. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): The ATMOSPHERE and PARADIGM-HF trials were sponsored by Novartis