Plasma Protein Profiling of Incident Cardiovascular Diseases: A Multisample Evaluation

Area of Science:

• Cardiovascular Science
• Proteomics
• Biomarker Discovery

Background:

• Cardiovascular diseases (CVD) represent a significant health burden.
• Proteomic profiling offers potential for discovering new CVD pathophysiological pathways and improving individual risk prediction.

Purpose of the Study:

• To investigate the plasma protein profile associated with the incidence of myocardial infarction, stroke, and heart failure.
• To identify novel protein biomarkers for CVD risk stratification.

Main Methods:

• Analysis of plasma protein levels in 11,869 individuals from four Swedish population-based cohorts (SIMPLER, ULSAM, EpiHealth, POEM).
• Utilized a discovery/validation approach to identify proteins associated with a composite CVD endpoint (myocardial infarction, stroke, heart failure).
• Performed meta-analyses for individual CVD outcomes and assessed prediction models using lasso selection.

Main Results:

• 42 proteins were associated with the composite CVD endpoint.
• Significant associations were found for myocardial infarction (49 proteins), ischemic stroke (34 proteins), and heart failure (109 proteins).
• Thirteen proteins, including kidney injury molecule 1 (KIM-1), urokinase plasminogen activator surface receptor, and adrenomedullin, were linked to all three outcomes and subclinical CVD markers.
• A panel of 11 proteins improved CVD prediction by 3.3% when added to traditional risk factors.

Conclusions:

• Proteomic profiling identified novel plasma proteins associated with myocardial infarction, stroke, and heart failure, suggesting common underlying pathophysiological mechanisms.
• Kidney injury molecule 1 (KIM-1), urokinase plasminogen activator surface receptor, and adrenomedullin emerged as potential early biomarkers for CVD.
• A selected panel of 11 proteins demonstrated potential to enhance CVD risk discrimination.