This proposal pairs existing analytical resources with clinical expertise at Mayo Clinic toward the goal of aiding the UDN in the diagnosis and mechanistic understanding of rare diseases. The overall goal is to apply state- of-the-art untargeted and targeted/quantitative metabolomics approaches, bioinformatics, and expert clinical interpretation to the biological samples collected within the established UDN pipeline.
The specific aims of the Mayo Clinic UDN Metabolomics Core are: 1) to collaborate with other UDN centers, 2) to perform global, untargeted metabolite profiling, 3) to perform targeted quantitative analysis of select metabolites, 4) to provide assay development capabilities, 5) to provide clinical expertise to the UDN, and 6) to provide access to our growing national network of metabolomics experts. Our approach to untargeted metabolite profiling involves 3 complementary analytical platforms for optimal coverage and annotation of metabolites by GC-MS, LC-MS/MS, and NMR spectroscopy. Our targeted quantitative approach will include key priority targets (i.e., glycans, lipids, and mitochondrial metabolites) as well as a wide breadth of other targetable metabolites that will provide crucial metabolic insights on a case-by-case basis. To accomplish these goals, we unite a diverse group of analytical chemists, physiologists, bioinformaticians, and clinicians as a single, integrated core that is prepared to contribute currently operational workflows and expertise to the UDN.
The Mayo Clinic UDN Metabolomics Core will contribute unique state-of-the art analytical facilities, informatics infrastructure, and clinical expertise to detect, quantitate, and interpret a wide range of diagnostic metabolite markers that will help diagnose diseases and lend important mechanistic insight into many rare diseases. Cutting-edge analytical techniques including mass spectrometry and NMR spectroscopy will be used to perform untargeted metabolite discovery screening as well as targeted quantitation of a selected groups of metabolites of interest. Analyses will be paired with specific clinical and informatics expertise to provide interpretation and context to the UDN at large.
