Harnessing the Plasma Proteome to Predict Mortality in Heart Failure Subpopulations

Circ Heart Fail. 2025 Apr;18(4):e011208. doi: 10.1161/CIRCHEARTFAILURE.123.011208. Epub 2025 Mar 7.

Abstract

Background: We derived and validated proteomic risk scores (PRSs) for heart failure (HF) prognosis that provide absolute risk estimates for all-cause mortality within 1 year.

Methods: Plasma samples from individuals with HF with reduced ejection fraction (HFrEF; ejection fraction <40%; training/validation n=1247/762) and preserved ejection fraction (HFpEF; ejection fraction ≥50%; training/validation n=725/785) from 3 independent studies were run on the SomaScan Assay measuring ≈5000 proteins. Machine learning techniques resulted in unique 17- and 14-protein models for HFrEF and HFpEF that predict 1-year mortality. Discrimination was assessed via C-index and 1-year area under the curve (AUC), and survival curves were visualized. PRSs were also compared with Meta-Analysis Global Group in Chronic HF (MAGGIC) score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) measurements and further assessed for sensitivity to disease progression in longitudinal samples (HFrEF: n=396; 1107 samples; HFpEF: n=175; 350 samples).

Results: In validation, the HFpEF PRS performed significantly better (P≤0.1) for mortality prediction (C-index, 0.79; AUC, 0.82) than MAGGIC (C-index, 0.71; AUC, 0.74) and NT-proBNP (PRS C-index, 0.76 and AUC, 0.81 versus NT-proBNP C-index, 0.72 and AUC, 0.76). The HFrEF PRS performed comparably to MAGGIC (PRS C-index, 0.76 and AUC, 0.83 versus MAGGIC C-index, 0.75 and AUC, 0.84) but had a significantly better C-Index (P=0.026) than NT-proBNP (PRS C-index, 0.75 and AUC, 0.78 versus NT-proBNP C-index, 0.73 and AUC, 0.77). PRS included known HF pathophysiology biomarkers (93%) and novel proteins (7%). Longitudinal assessment revealed that HFrEF and HFpEF PRSs were higher and increased more over time in individuals who experienced a fatal event during follow-up.

Conclusions: PRSs can provide valid, accurate, and dynamic prognostic estimates for patients with HF. This approach has the potential to improve longitudinal monitoring of patients and facilitate personalized care.

Keywords: cardiovascular diseases; heart failure; natriuretic peptide, brain; prognosis; proteomics.

MeSH terms

  • Aged
  • Biomarkers / blood
  • Disease Progression
  • Female
  • Heart Failure* / blood
  • Heart Failure* / diagnosis
  • Heart Failure* / mortality
  • Heart Failure* / physiopathology
  • Humans
  • Male
  • Middle Aged
  • Natriuretic Peptide, Brain / blood
  • Peptide Fragments / blood
  • Predictive Value of Tests
  • Prognosis
  • Proteome* / metabolism
  • Proteomics* / methods
  • Risk Assessment
  • Risk Factors
  • Stroke Volume / physiology

Substances

  • Biomarkers
  • Proteome
  • Natriuretic Peptide, Brain
  • pro-brain natriuretic peptide (1-76)
  • Peptide Fragments