Metabonomic characterization of early atherosclerosis in hamsters with induced cholesterol

Abstract

Atherosclerosis is a complicated and multifactorial disease, induced not only by genotype, but also, even more importantly, by environmental factors. Study on the metabolic perturbation of endogenous compounds may offer deeper insight into development of atherosclerosis. Gas chromatography/mass spectrometry (GC/MS)-based metabonomics was used to profile a metabolic fingerprint of serum obtained from hamsters with induced cholesterol. The deconvoluted GC/MS data were processed by multivariate statistical analysis tools, such as principal component analysis (PCA) and partial least squares projection to latent structure and discriminant analysis (PLS-DA). For the first time we showed a time-dependent development of the model animal from normal to hypercholesterolaemia, and further to early atherosclerosis. Twenty-one compounds were identified as markers involved in the development to atherosclerosis. Identification of the compounds suggests that amino acid metabolism and fatty acid oxidation are significantly perturbed following cholesterol overloading. The data provide novel information to approach the pathophysiological processes of the hypercholesterolaemia and atherosclerosis disease continuum.

Keywords::

• Metabonomics
• early atherosclerosis
• hypercholesterolaemia
• GC/MS
• multivariate statistical analysis

Acknowledgements

The authors thank Professor Lin Xie and graduate students, Shihai Yan, Nanqi Shao and Enze Guan, for their technical assistance. We also thank Beth Shoshana Pecora, Virginia Commonwealth University, for the revision of the paper. This study was financially supported by the National Nature Science Fund (30572228 and 30630076), the Jiangsu Nature Science Fund (BK2005098), and the Jiangsu International Cooperation Fund (BZ2006049).

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