Improved cholesterol phenotype analysis by a model relating lipoprotein life cycle processes to particle size
Autor: | Ben van Ommen, Jan van der Greef, Daniël B. van Schalkwijk, Albert A. de Graaf, Huub C. J. Hoefsloot, Niek C. A. van de Pas, Andreas P. Freidig, Kees van Bochove, Louis M. Havekes, Patrick C.N. Rensen |
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Přispěvatelé: | TNO Kwaliteit van Leven, Biosystems Data Analysis (SILS, FNWI) |
Rok vydání: | 2009 |
Předmět: |
medicine.medical_specialty
Lipoproteins data analysis Data analysis lipoprotein lipase Familial hypercholesterolemia QD415-436 Physiological Sciences Biology Models Biological Biochemistry chemistry.chemical_compound Endocrinology Internal medicine medicine Humans Particle Size Triglycerides Lipoprotein lipase Genetic polymorphism Triglyceride Cholesterol stable isotope flux data mathematical modeling Hepatic lipase Cell Biology medicine.disease hepatic lipase Kinetics Phenotype chemistry kinetics Health Stable isotope flux data lipids (amino acids peptides and proteins) Mathematical modeling Particle size Flux (metabolism) Lipoprotein Research Article |
Zdroj: | Journal of Lipid Research, 12, 50, 2398-2411 Journal of Lipid Research, Vol 50, Iss 12, Pp 2398-2411 (2009) Journal of Lipid Research, 50(12), 2398-2411. American Society for Biochemistry and Molecular Biology Inc. |
ISSN: | 0022-2275 2398-2411 |
Popis: | 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 profi le data and deriving rates of various lipolysis and uptake processes if an independent production estimate is given. © 2009 by the American Society for Biochemistry and Molecular Biology, Inc. |
Databáze: | OpenAIRE |
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