In 2022, heart disease was the leading cause of death in the United States. Low-density lipoproteins (LDL) are a significant contributor to atherosclerotic plaque and their concentration in the blood is targeted as a marker for cardiovascular disease (CVD) risk. Our goal is to create an empirical model that uses solvent paramagnetic relaxation effects (sPRE) of gadavist on an observed NMR signal to classify vesicle size of lipoprotein particles (LDL, HDL, and VLDL). sPRE effects on the NMR signal of a reporter molecule within the vesicles can be studied by developing vesicles that resemble lipoprotein particle sizes. It is anticipated that the reporter compound in smaller particles will experience a larger sPRE effect, while the reporter in larger particles will experience a smaller sPRE effect. Unilamellar vesicles of various diameters will be used to study how a paramagnetic agent, Gadavist®, impacts T 2 relaxation relative to particle size. Vesicles were prepared using POPC and cholesterol and loaded with a reporter molecule. Loaded vesicles were separated from the free reporter using fast protein liquid chromatography (FPLC). Vesicle preparation and quality controls to track vesicle size and determine lipid concentration after FPLC are discussed here. 13 C-glucose was added to lipid films during the hydration step as the NMR sensitive reporter molecule. FPLC (S200 10/300 GL column) was used to separate the vesicles from free glucose. Separation of glucose-containing vesicles from free glucose was achieved using an optimal column volume of 24 mL (h = 300 mm, d = 10 mm). Lipid concentration was quantified using a standard curve based on the 31 P signal of multiple concentrations of POPC in “100%” methanol-D 4 .
Ahmed et al. (Sun,) studied this question.