Metabonomic profiling of diet-induced hyperlipidaemia in a rat model

Abstract

This study describes the metabolic profiles of the development of hyperlipidaemia in a rat model, utilizing metabonomics by gas chromatography–mass spectrometry (GC-MS) determination coupled with multivariate statistical analysis. Rat plasma samples were collected before and during a high-lipid diet at days 0, 7, 14, 21 and 28, and were analysed for lipid levels using kit assays or metabonomics using GC-MS. Forty-one endogenous metabolites were separated, identified and quantified using GC-MS. The data matrix was processed by principal component analysis or partial least squares discriminant analysis. Dynamic modification of the rat metabonome can be clearly identified and tracked at different stages of hyperlipidaemia in the rat model. Potential biomarkers, including β-hydroxybutyrate, tyrosine and creatinine, were identified. The current work suggests that metabonomics is able to provide an overview of biochemical profiles of disease progress in animal models. Using a metabonomic approach to identify physiopathological states promises to establish a new methodology for the early diagnosis of human diseases.

Keywords::

• Metabonomics
• hyperlipidaemia
• GC-MS
• principal component analysis
• partial least squares discriminant analysis
• early diagnosis

Acknowledgment

The study was financially supported with National Nature Science Fund (30873112) and the sixth Talent Peak Project of Jiangsu Province (07-C-018).

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.