The goal of the proposed research is to develop a clinical metabolomics platform using highly sensitive technologies with a wide dynamic range for identification and quantification of comprehensive subclasses of diverse metabolites in human body fluids, cells and tissues from healthy and diseased individuals. The research will focus entirely on human health conditions with the ultimate goal of providing a novel tool to understand disease processes, predict their course and outcome, evaluate their response to therapy, and predict predisposition to diseases. Key components of the proposed clinical metabolomics platform are: NMR and mass spectroscopy, and their combined use in a novel LC-NMR-ESI-TOF-MS instrument, available to us through our technology partners: Bruker Biospin and Bruker Daltonics. We will develop an integrated arsenal of robust tools such as trap-column solid phase extraction devices that will improve LC technology, novel acquisition/processing methods to increase NMR sensitivity and resolution, internal standard mixtures (ISM) to allow quantification in MS analyses, and expert analysis systems. The development of the platform will be carried out in the context of chronic myelogeneous leukemia (CML). Because of its characteristic t (9; 22) translocation, which allows an unambiguous cytogenetic identification of CML cell, this disease is an ideal model to test and validate the clinical metabolomics platform, as proposed here. The planned research will be a joint effort between the laboratory of the PI and the Laboratory of Translational Research, both at Harvard Medical School, and Bruker Biospin and Bruker Daltonics. The four sites will bring complementary expertise for access to CML blood and urine samples, NMR, mass spectroscopy and systems technology. The research will be pursued with four specific aims:
Specific Aim 1 is to develop cell separation, fractionation and purification methods for clinical metabolomics studies.
Specific Aim 2 is to develop integrated experimental methods for clinical metabolics profiling, and rapid identification and quantification of metabolites in human cells and body fluids.
Specific Aim 3 is to develop statistical methods and algorithms for integrated NMR and MS data analysis, metabolite identification and correlations with health conditions.
Specific Aim 4 is to validate the developed clinical metabolomics platform by assessing its power to detect CML-specific metabolic profiles and biomarkers in samples of cells, plasma and urine.
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