In a previous cross-sectional study, we identified a multidimensional urinary classifier (HF1), which was associated with left ventricular dysfunction. We investigated whether HF1 predicts cardiovascular end points over and beyond traditional risk factors. In 791 randomly recruited Flemish (mean age, 51.2 years; 50.6% women), we quantified HF1 by capillary electrophoresis coupled with mass spectrometry. In addition, we measured cardiovascular risk factors. HF1 averaged -0.97 U (range, -3.26 to 2.60). Over 6.1 years (median), 35 participants died and 63, 45, and 22 experienced fatal or nonfatal cardiovascular, cardiac, or coronary events, respectively. The incidence of fatal combined with nonfatal cardiovascular and cardiac end points, standardized for sex and age, increased across thirds of the HF1 distribution (P≤0.014), whereas trends for all-cause mortality and coronary events were nonsignificant (P≥0.10). The multivariable-adjusted hazard ratios (+1-SD) were 1.30 (95% confidence interval, 1.03-1.65; P=0.029) and 1.39 (1.06-1.84; P=0.018) for cardiovascular and cardiac events in relation to HF1. For systolic pressure, the corresponding estimates were 0.97 (0.74-1.28; P=0.85) and 0.93 (0.67-1.29; P=0.66), respectively. The HF1 upper thresholds optimized by maximizing Younden's index were -0.50 and -0.36 U for cardiovascular and cardiac end points, respectively. Prognostic accuracy significantly (P≤0.006) improved by adding HF1 to Cox models already including the other baseline predictors. Sensitivity analyses, from which we excluded 71 participants with previous cardiovascular disease, were confirmatory. In conclusion, over a 6-year period, the urinary proteome, but not systolic pressure, predicted cardiovascular and cardiac disease.
Keywords: biomarker; cardiovascular disease; morbidity; mortality; proteomics.
© 2015 American Heart Association, Inc.