A Proteomic Platform to identify and Validate Biomarkers in Metabolic Syndrome and Coronary Artery Disease

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Blood plasma/serum has remained a major sample source for the detection of disease biomarker candidates with its easy accessibility and measurable tissue-derived proteins that hold potential to uncover physiological and pathological changes during diseases. Proteomics-based biomarker discovery using plasma/serum, however, is severely limited by the high complexity and dynamic range of protein concentrations (10-12 orders of magnitude). Presently, a majority of plasma/serum proteomic strategies are lack of adequate reproducibility, sensitivity, and robustness for clinical tests. Solutions for these serious technological barriers to develop a reliable detection platform toward clinical implementation are elusive. The long term goal of this project is to establish a robust proteomic platform that is translational, sensitive, and reproducible for biomarker discovery, verification and validation, with an emphasis on the identification and validation of plasma biomarkers for metabolic syndrome and early detection of coronary artery disease (CAD). We propose to develop a distinctive platform based on metal ion functionalized soluble nanopolymers for efficient and selective isolation of subsets of low abundant plasma proteins. We will test this approach by focusing on Ossabaw swine as our model system and will establish protocols that will ultimately provide a powerful method for any biofluid-based biomarker discovery. We propose to profile plasma proteomes as a function of feeding time and to correlate with physiological and pathological parameters over the period in which the Ossabaw swine develop metabolic syndrome. There is an increasingly urgent and strong push of proteomic discoveries to clinical applications. This project is based on a distinctive new concept and once developed, it will dramatically simplify the procedure and enhance our ability to sensitively identify candidate markers. As a consequence, the results of this study will have an important positive impact, not only on the development of novel tools for proteomics-based biomarker discovery, but also toward improving disease therapeutics and facilitating more effective diagnosis.