Urinary proteomic biomarkers to predict cardiovascular events

Purpose: We have previously demonstrated associations between the urinary proteome profile and coronary artery disease (CAD) in cross-sectional studies. Here we evaluate the potential of a urinary proteomic panel as a predictor of CAD in the Hypertensive Atherosclerotic Cardiovascular Disease (HACVD) sub-study population of the ASCOT study.<p></p> Experimental design: Thirty-seven cases with primary CAD endpoint were matched for sex and age to controls who had not reached a CAD endpoint during the study. Spot urine samples were analysed using capillary electrophoresis (CE) coupled to Micro-TOF mass spectrometry (MS). A previously developed 238-marker CE-MS model for diagnosis of CAD (CAD238) was assessed for its predictive potential.<p></p> Results: Sixty urine samples (32 cases; 28 controls; 88% male, mean age 64±5 years) were analysed. There was a trend towards healthier values in controls for the CAD model classifier (-0.432±0.326 vs -0.587±0.297, P = 0.170), and the CAD model showed statistical significance on Kaplan-Meier survival analysis P = 0.021. We found 190 individual markers out of 1501 urinary peptides that separated cases and controls (AUC>0.6). Of these, 25 peptides were also components of CAD238.<p></p> Conclusion & clinical relevance: A urinary proteome panel originally developed in a cross-sectional study predicts CAD endpoints independent of age and sex in a well controlled prospective study.<p></p&gt