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Improved Estimation of Human Lipoprotein Kinetics with Mixed Effects Models

Journal article
Authors Martin Berglund
Martin Adiels
M. R. Taskinen
Jan Borén
Bernt Wennberg
Published in PLoS ONE
Volume 10
Issue 9
Pages artikel nr e0138538
ISSN 1932-6203
Publication year 2015
Published at Department of Mathematical Sciences
Institute of Medicine, Department of Molecular and Clinical Medicine
Pages artikel nr e0138538
Language en
Links dx.doi.org/10.1371/journal.pone.013...
https://gup.ub.gu.se/file/170733
Subject categories Mathematics

Abstract

Mathematical models may help the analysis of biological systems by providing estimates of otherwise un-measurable quantities such as concentrations and fluxes. The variability in such systems makes it difficult to translate individual characteristics to group behavior. Mixed effects models offer a tool to simultaneously assess individual and population behavior from experimental data. Lipoproteins and plasma lipids are key mediators for cardiovascular disease in metabolic disorders such as diabetes mellitus type 2. By the use of mathematical models and tracer experiments fluxes and production rates of lipoproteins may be estimated. We developed a mixed effects model to study lipoprotein kinetics in a data set of 15 healthy individuals and 15 patients with type 2 diabetes. We compare the traditional and the mixed effects approach in terms of group estimates at various sample and data set sizes. We conclude that the mixed effects approach provided better estimates using the full data set as well as with both sparse and truncated data sets. Sample size estimates showed that to compare lipoprotein secretion the mixed effects approach needed almost half the sample size as the traditional method.

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