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Composition and lipid spatial distribution of HDL particles in subjects with low and high HDL-cholesterol
Authors:Laxman Yetukuri  Sanni S?derlund  Artturi Koivuniemi  Tuulikki Sepp?nen-Laakso  Perttu S Niemel?  Marja Hyv?nen  Marja-Riitta Taskinen  Ilpo Vattulainen  Matti Jauhiainen  Matej Ore?i?
Institution:1. VTT Technical Research Centre of Finland, Espoo, Finland;2. Division of Cardiology, Department of Medicine, University of Helsinki, Helsinki, Finland;4. Department of Physics, Tampere University of Technology, Tampere, Finland;7. Department of Physics, University of Oulu, Finland;11. Department of Physics, Aalto University School of Science and Engineering, Espoo, Finland;8. MEMPHYS – Center for Biomembrane Physics, University of Southern Denmark, Odense, Denmark;71. National Institute for Health and Welfare, Helsinki, Finland;112. Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
Abstract:A low level of high density lipoprotein cholesterol (HDL-C) is a powerful risk factor for cardiovascular disease. However, despite the reported key role of apolipo-proteins, specifically, apoA-I, in HDL metabolism, lipid molecular composition of HDL particles in subjects with high and low HDL-C levels is currently unknown. Here lipidomics was used to study HDL derived from well-characterized high and low HDL-C subjects. Low HDL-C subjects had elevated triacylglycerols and diminished lysophosphatidylcholines and sphingomyelins. Using information about the lipid composition of HDL particles in these two groups, we reconstituted HDL particles in silico by performing large-scale molecular dynamics simulations. In addition to confirming the measured change in particle size, we found that the changes in lipid composition also induced specific spatial distributions of lipids within the HDL particles, including a higher amount of triacylglycerols at the surface of HDL particles in low HDL-C subjects. Our findings have important implications for understanding HDL metabolism and function. For the first time we demonstrate the power of combining molecular profiling of lipoproteins with dynamic modeling of lipoprotein structure.
Keywords:high density lipoprotein  lipidomics  lipid metabolism  molecular dynamics
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