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Published in: Nutrition & Metabolism 1/2010

Open Access 01-12-2010 | Research

High throughput prediction of chylomicron triglycerides in human plasma by nuclear magnetic resonance and chemometrics

Authors: Francesco Savorani, Mette Kristensen, Flemming H Larsen, Arne Astrup, Søren B Engelsen

Published in: Nutrition & Metabolism | Issue 1/2010

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Abstract

Background

The lipid content of the chylomicrons is a key biomarker and risk factor of cardiovascular diseases and for the understanding of obesity. A high throughput determination of chylomicrons in human blood plasma is outlined.

Methods

The new method, which uses a combination of Nuclear Magnetic Resonance (NMR) analysis and multivariate calibration analysis (chemometrics), is based on a correlation analysis towards the established standard method (ultracentrifugation and colorimetric test kit) and enables extraordinarily fast, inexpensive, and robust prediction of triglyceride (TG) content in chylomicrons. It is the position and shape of the complex lipid methylene resonance band that determines the chylomicron TG status and this information is extracted by the multivariate regression method.

Results

The resulting method is a relatively simple multivariate model that facilitates parsimonious and accurate prediction of chylomicron lipids from NMR spectra of blood. The chemometric model predicts the chylomicron TG content with a correlation coefficient (R) of 0.96 when plotted against density gradient ultracentrifugation data.

Conclusions

The new rapid method facilitates large scale clinical and nutritional trials with inclusion of diagnostics of chylomicron status and thus creates new opportunities for research in lifestyle diseases and obesity.
Appendix
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Metadata
Title
High throughput prediction of chylomicron triglycerides in human plasma by nuclear magnetic resonance and chemometrics
Authors
Francesco Savorani
Mette Kristensen
Flemming H Larsen
Arne Astrup
Søren B Engelsen
Publication date
01-12-2010
Publisher
BioMed Central
Published in
Nutrition & Metabolism / Issue 1/2010
Electronic ISSN: 1743-7075
DOI
https://doi.org/10.1186/1743-7075-7-43

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