Proteomic profiling to identify prognostic biomarkers in heart failure

Area of Science:

• Cardiology
• Proteomics
• Biomarker Discovery

Background:

• Predicting mortality risk in left ventricular systolic dysfunction (LVSD) is crucial for optimizing implantable cardioverter defibrillator (ICD) therapy selection.
• The utility of proteomic approaches for identifying prognostic biomarkers in LVSD remains largely unexplored.

Purpose of the Study:

• To identify serum biomarkers associated with LVSD using proteomic techniques.
• To prospectively evaluate the prognostic value of identified biomarkers for mortality and ICD therapy outcomes.

Main Methods:

• Serum samples from patients with (n=78) and without (n=45) systolic heart failure (SHF) were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS).
• Differentially expressed protein peaks were identified and then prospectively tested for their ability to predict all-cause mortality and appropriate ICD therapy in LVSD patients (n=141).

Main Results:

• Six protein peaks were found to be differentially expressed in SHF patients in both discovery and validation sets.
• During a mean follow-up of 15 months, five of the six identified proteomic biomarkers predicted all-cause mortality.
• None of the identified biomarkers predicted appropriate ICD therapy outcomes.

Conclusions:

• The SELDI proteomic approach serves as a valuable high-throughput screening tool for identifying potentially prognostic protein peaks in LVSD patients.
• These findings provide proof-of-principle for using proteomics to discover novel biomarkers for risk stratification in LVSD.