Prediction of coronary artery disease using urinary proteomics

Abstract

Aims Coronary artery disease (CAD) is multifactorial, caused by complex pathophysiology, and contributes to a high burden of mortality worldwide. Urinary proteomic analyses may help to identify predictive biomarkers and provide insights into the pathogenesis of CAD. Methods Urinary proteome was analysed in 965 participants using capillary electrophoresis coupled with mass spectrometry. A prote- and results omic classifier was developed in a discovery cohort with 36 individuals with CAD and 36 matched controls using the support vector machine. The classifier was tested in a validation cohort with 115 individuals who progressed to CAD and 778 controls and compared with two previously developed..