Lipoprotein analysis by 2d diffusion-ordered 1h-nmr spectroscopy

Identificador:  TDX:2892

Handle: https://hdl.handle.net/20.500.11797/TDX2892

Autores:  Amigó Grau, Núria

Resumen:
The need for predictors of cardiovascular disease is increasing due to the pandemic levels that metabolic disorders are achieving. One of the main areas where new biomarkers can be looked for is in the lipids and lipoproteins field. NMR spectroscopy appears to be a suitable analytical tool to develop novel methodologies, which will aid in the assessment and management of cardiovascular events and cardio-metabolic disease, due to its sensitivity to the lipoprotein content and size, robustness and the possibility of automation. Part of the research presented in this thesis is focused on the development and industrialization of the Liposcale test: an advanced lipoprotein test based on 2D diffusion ordered NMR spectroscopy (2D-DOSY NMR), born in a pure research framework, aiming to prepare it for the clinical use. Additionally, the scientific interest for the results derived from the lipoprotein characterization by 2D-DOSY NMR has been demonstrated over the course of the present thesis as reflected by the participation in several research studies from diverse areas of application, in which the test has given insights into the lipoprotein metabolism. Alternatively, we have used 2D-DOSY NMR experiments for the study of the HDL isolated fraction for the evaluation and monitoring of diabetic dislipemia in combination with two other biophysical techniques -Atomic Force Microscopy (AFM) and fluorimetry, to explore lipoprotein properties beyond lipid content, such as the molecular lipoprotein structure and surface; favoring to understand their functionality in processes that deal with metabolic disorders. Finally, the thesis explores how non-pharmacological nutritional interventions and diet modulates the lipoprotein profile; and how its characterization by using NMR can be used as an alternative to the traditional lipid characterization being sensitive to the lipoprotein distribution between subfractions and size, and therefore a better tool to evaluate different types of interventions, both pharmacological and nutritional.