Aims: Urine proteome analysis (UPA) has already provided accurate discriminatory patterns of urinary peptides for renal disease, coronary artery disease, and asymptomatic LV diastolic dysfunction. UPA has now been used to characterize a discriminatory peptide biomarker pattern and establish a diagnostic classifier for heart failure patients with reduced ejection fraction (HFrEF) in the presence of chronic kidney disease (CKD).
Methods and results: We analysed the urine proteome profiles obtained by capillary electrophoresis online coupled to micro-TOF (time of flight) mass spectrometry of 126 individuals, 59 HFrEF patients and 67 controls matched for age, sex, and renal function. In total, 107 significant discriminatory peptides were identified and used to establish a support vector machine-based classifier that was successfully applied to a test set of 25 HFrEF patients and 33 controls, achieving 84% sensitivity and 91% specificity. The majority of sequenced peptides were fragments of collagen type I and III.
Conclusion: UPA was able to identify a set of HFrEF-specific urinary peptide biomarkers on a background of CKD that were successfully utilized to establish a syndrome's classifier.
Keywords: Biomarkers; Heart failure; Proteomics; Urine.
© 2016 The Authors. European Journal of Heart Failure © 2016 European Society of Cardiology.