Clinical investigation meets computer simulation to analyze risk factor of heart disease

German researchers at the Charité – Universitätsmedizin Berlin and the Max-Delbrück-Center Berlin have developed a novel, computer-based strategy to study plasma lipoprotein profiles considered a major predictor of cardiovascular disease (CVD). This work was in part associated to the German Systems Biology Initiative HepatoSys. Clinical data of lipoprotein profiles were generated in collaboration with the University Medical Center Freiburg. Details are published May 23rd in the open-access journal PLoS Computational Biology.

Lipoproteins are the “container ships” in our blood that transport lipids (fats) such as cholesterol and triglycerides to various tissues; they differ largely in size and “cargo” composition. Abnormalities in the amount of certain lipoprotein fractions are considered a major risk factor for atherosclerosis and CVD. To identify patients at risk for CVD, selected lipoprotein fractions - “bad” Low Density Lipoproteins (LDL) and “good” High Density Lipoproteins (HDL) - are routinely monitored in clinical practice (lipoprotein profile). The decrease of LDL cholesterol is a principal target in cardiovascular preventive strategies. Growing evidence claims that evaluating the lipoprotein profile in greater detail (e.g. looking at subfractions of LDL and HDL) may provide more reliable prognostic information than routine measurement of LDL cholesterol levels, but this needs elaborate and expensive work.

Katrin Hübner and colleagues, therefore, conceived of designing a mathematical model to provide computer calculations of lipoprotein profiles which take into account the entire “fleet” of lipoproteins in blood plasma by simulating every single lipoprotein (“ship”). This way, studying lipoprotein profiles in any desired detail is possible. The model may also be broadly applied to infer relationships between a patient's lipoprotein profile and the underlying biochemical processes.

The calculations were verified by comparing them with clinically measured lipoprotein profiles of healthy subjects and pathological cases of known lipid disorders. The researchers show that more detailed lipoprotein profiles can reveal possibly clinically-relevant abnormalities in the lipid values which would remain undetected by evaluating only LDL and HDL.

Together with independent information on diet and genetic variations this increases the potential for patient-oriented diagnosing of molecular causes for observed abnormal lipoprotein profiles.

PLEASE ADD THIS LINK TO THE PUBLISHED ARTICLE IN ONLINE VERSIONS OF YOUR REPORT: http://www.ploscompbiol.org/doi/pcbi.1000079 (link will go live on Friday, May 23)

CITATION: Hübner K, Schwager T, Winkler K, Reich J-G, Holzhu¨ tter H-G (2008) Computational Lipidology: Predicting Lipoprotein Density Profiles in Human Blood Plasma. PLoS Comput Biol 4(5): e1000079. doi:10.1371/journal.pcbi.1000079

PRESS-ONLY PDF: http://www.plos.org/press/plcb-04-05-23-huebner.pdf

CONTACT:

Katrin Hübner
University of Heidelberg
Modeling biological processes
Bioquant, BQ 0018 AG Kummer
Im Neuenheimer Feld 267
69120 Heidelberg, Germany
phone: +49 6221 54 51 276
fax: +49 6221 54 51 483
email: katrin.huebner@bioquant.uni-heidelberg.de

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