Urinary proteomic biomarkers to predict cardiovascular events

Catriona E. Brown, Nina S. McCarthy, Alun D. Hughes, Peter Sever, Angelique Stalmach, William Mullen, Anna F. Dominiczak, Naveed Sattar, Harald Mischak, Simon Thom, Jamil Mayet, Alice V. Stanton, Christian Delles

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

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) substudy population of the Anglo-Scandinavian Cardiac Outcomes Trial study. 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 analyzed using CE coupled to Micro-TOF MS. A previously developed 238-marker CE-MS model for diagnosis of CAD (CAD238) was assessed for its predictive potential. Results: Sixty urine samples (32 cases; 28 controls; 88% male, mean age 64 ± 5 years) were analyzed. There was a trend toward healthier values in controls for the CAD model classifier (-0.432 ± 0.326 versus -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. Conclusion and 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.

Original languageEnglish
Pages (from-to)610-617
Number of pages8
JournalProteomics - Clinical Applications
Volume9
Issue number5-6
DOIs
Publication statusPublished - 1 Jun 2015

Keywords

  • Biomarker
  • Cardiovascular risk
  • Urinary proteomics

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