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Molecular & Cellular Proteomics 7:290-298, 2008.
© 2008 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Urinary Proteomic Biomarkers in Coronary Artery Disease^*,S

From the ^a British Heart Foundation (BHF) Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8TA, United Kingdom, ^d Mosaiques Diagnostics and Therapeutics AG, 30625 Hannover, Germany, ^e Departments of Chemistry and Biomolecular Chemistry, University of Wisconsin, Madison, Wisconsin 53706, ^g Thermo Fisher Scientific, 28199 Bremen, Germany, ^h Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom, ⁱ Department of Medicine IV, Nephrology and Hypertension, University of Erlangen-Nürnberg, 91054 Erlangen, Germany, ^j Baker Heart Research Institute, Melbourne, Victoria 8008, Australia, and ^k The Beatson Institute for Cancer Research, Glasgow G61 1BD, United Kingdom

Urinary proteomics is emerging as a powerful non-invasive tool for diagnosis and monitoring of variety of human diseases. We tested whether signatures of urinary polypeptides can contribute to the existing biomarkers for coronary artery disease (CAD). We examined a total of 359 urine samples from 88 patients with severe CAD and 282 controls. Spot urine was analyzed using capillary electrophoresis on-line coupled to ESI-TOF-MS enabling characterization of more than 1000 polypeptides per sample. In a first step a "training set" for biomarker definition was created. Multiple biomarker patterns clearly distinguished healthy controls from CAD patients, and we extracted 15 peptides that define a characteristic CAD signature panel. In a second step, the ability of the CAD-specific panel to predict the presence of CAD was evaluated in a blinded study using a "test set." The signature panel showed sensitivity of 98% (95% confidence interval, 88.7–99.6) and 83% specificity (95% confidence interval, 51.6–97.4). Furthermore the peptide pattern significantly changed toward the healthy signature correlating with the level of physical activity after therapeutic intervention. Our results show that urinary proteomics can identify CAD patients with high confidence and might also play a role in monitoring the effects of therapeutic interventions. The workflow is amenable to clinical routine testing suggesting that non-invasive proteomics analysis can become a valuable addition to other biomarkers used in cardiovascular risk assessment.

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