1H NMR Spectroscopy of Lipoproteins-When Size Matters

Lipoproteins are a wide class of biological structures represented by micellar aggregates of biomolecules that allow the fat content to be transported through the hydrophilic blood environment. When analyzing lipoproteins, NMR spectroscopy represents the only analytical platform capable of obtaining signals from their constituent molecules while still structured in the physiological micellar form. In comparison to the UC reference method, NMR spectroscopy boasts drastically shorter times for the analysis and much smaller samples. Furthermore, the manual slicing requested for separating the lipoprotein subclasses in UC, results in larger analytical errors and reproducibility problems which are significantly reduced when NMR analysis is adopted. It is also possible to sensitize the NMR measurements to translational diffusion which can be modelled to achieve an even better definition of the lipoprotein particle distribution. On the downside, the NMR signals from the lipoprotein main constituents, the triglycerides, give rise to very broad overlapping signals, combined by all the contributing lipoprotein subclasses, which cannot be efficiently solved by classical statistical methods. However because of the increased computational power of modern computers, a chemometric approach on the full featured, full resolution NMR spectra has been attempted with great success. The slightly different peak shapes and shifts are modelled in a multivariate fashion providing detailed information on the lipoprotein composition in a continuous fashion. The new NMR-based high-throughput method for lipoprotein profiling has great potential for future nutritional metabolomics studies focused on developing stratified nutrition for different populations. The new iPLS-based method enables extraordinarily fast, inexpensive, and robust prediction of absorption kinetics of chylomicrons. The high-throughput nature of the new lipoprotein profiling method will allow real-time measurements of the return to normal homeostasis after a food challenge and thus provide a much better understanding of food digestion and health than the current static methods. It creates new opportunities for research in lifestyle diseases and obesity, becoming a valuable tool in nutritional research for assessment of absorption of exogenous diet-derived lipids.