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Papers In Press, published online ahead of print December 1, 2009
J. Lipid Res., doi:10.1194/jlr.M800354-JLR200

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Journal of Lipid Research, Vol. 50, 2398-2411, December 2009
Copyright © 2009 by American Society for Biochemistry and Molecular Biology

Improved cholesterol phenotype analysis by a model relating lipoprotein life cycle processes to particle size^[S]

Daniël B. van Schalkwijk^1,*,, Albert A. de Graaf^*, Ben van Ommen^*, Kees van Bochove^*, Patrick C. N. Rensen, Louis M. Havekes^*,, Niek C. A. van de Pas^*, Huub C. J. Hoefsloot^**, Jan van der Greef^*, and Andreas P. Freidig

^* TNO Quality of Life, Business Unit Biosciences, Zeist and Leiden, The Netherlands
Leiden Amsterdam Centre for Drug Research (LACDR), Analytical Sciences Division, Leiden, The Netherlands
Departments of General Internal Medicine, Endocrinology and Metabolic Diseases and Cardiology, Leiden University Medical Centre (LUMC), Leiden, The Netherlands
^** Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
Amsterdam Molecular Therapeutics (AMT), Amsterdam, The Netherlands

¹ To whom correspondence should be addressed. e-mail: daan.vanschalkwijk{at}tno.nl

Increased plasma cholesterol is a known risk factor for cardiovascular disease. Lipoprotein particles transport both cholesterol and triglycerides through the blood. It is thought that the size distribution of these particles codetermines cardiovascular disease risk. New types of measurements can determine the concentration of many lipoprotein size-classes but exactly how each small class relates to disease risk is difficult to clear up. Because relating physiological process status to disease risk seems promising, we propose investigating how lipoprotein production, lipolysis, and uptake processes depend on particle size. To do this, we introduced a novel model framework (Particle Profiler) and evaluated its feasibility. The framework was tested using existing stable isotope flux data. The model framework implementation we present here reproduced the flux data and derived lipoprotein size pattern changes that corresponded to measured changes. It also sensitively indicated changes in lipoprotein metabolism between patient groups that are biologically plausible. Finally, the model was able to reproduce the cholesterol and triglyceride phenotype of known genetic diseases like familial hypercholesterolemia and familial hyperchylomicronemia. In the future, Particle Profiler can be applied for analyzing detailed lipoprotein size profile data and deriving rates of various lipolysis and uptake processes if an independent production estimate is given.

Supplementary key words kinetics • data analysis • mathematical modeling • stable isotope flux data • lipoprotein lipase • hepatic lipase • genetic polymorphism

Abbreviations: Apo, apolipoprotein; GPIHBP1, glycosylphosphatidylinositol-anchored HDL-binding protein 1; HSPG, heparan sulfate proteoglycans; IDL, intermediate density lipoprotein; LRP, low density lipoprotein receptor-related protein; SR-BI, scavenger receptor class B type I

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