Aptamer Proteomics for Biomarker Discovery in Heart Failure with Reduced Ejection Fraction

Abstract Background Systematically characterizing associations between circulating proteins and risk for subsequent clinical events may improve clinical risk prediction and shed light on unrecognized biological pathways in heart failure (HF). Large-scale assays measuring thousands of proteins now enable broad proteomic investigation in clinical trials. Methods Serum levels of 4076 proteins were measured at baseline in the ATMOSPHERE (n=1258, 487 events over 6 years) and PARADIGM-HF (n=1257, 287 events over 4 years) trials of chronic HF with reduced ejection fraction using a modified aptamer-based proteomics assay. Proteins associated with the primary endpoint of HF hospitalization or cardiovascular death were identified in the ATMOSPHERE discovery cohort by Cox regression adjusted for age, sex, treatment arm, and anticoagulant use (false discovery rate<0.05), and were 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) immunoassay. For proteins that were associated with the primary endpoint, two-sample Mendelian randomization was performed using genetic and outcome data from both trials and protein quantitative trait loci from deCODE to infer causal associations. Results We identified 377 serum proteins that were associated with the primary endpoint in ATMOSPHERE and replicated 167 in PARADIGM-HF. Prognostic proteins included known HF biomarkers such as Growth Differentiation Factor 15, NT-BNP, 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=2×10 −17 ). A 64-protein risk score derived in ATMOSPHERE predicted the primary endpoint 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). Genetically controlled levels of BNP, WISP2, FSTL1, and CTSS were associated with the primary endpoint by Mendelian randomization. Conclusions We identified SVEP1, an extracellular matrix protein known to cause inflammation in vascular smooth muscle cells, as a new HF biomarker associated with risk of hospitalization or death. A 64-protein score improved risk discrimination compared with NT-proBNP and may assist in identifying high-risk patients.

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