Plasma fatty acids metabolic profiling analysis of coronary heart disease based on GC–MS and pattern recognition

Abstract

A simple approach for comprehensive profiling of fatty acids in human plasma based on gas chromatography–mass spectrometry (GC–MS) was described and validated. With this method, plasma fatty acid metabolic profiles of 23 coronary heart disease (CHD) patients and 25 healthy subjects were determined. Pattern recognition technology was used to establishing differences in the metabolic profiles of these two groups. Furthermore, CHD patients with two different patterns in Traditional Chinese Medicine clinical practices could be classified by the corresponding metabolic profiles, and several potential biomarkers were discussed.

Introduction

Coronary heart disease (CHD), as one of the most mortal diseases, is afflicting millions of people every year [1], [2], [3]. Till now, researchers have paid close attention to the correlation between blood lipid level and CHD. And plasma fatty acids were emphasized, for they not only provide an important energy source as nutrients, but also act as signaling molecules in various cellular processes in cardiovascular risks [4].

Nowadays, with the development of system biology, novel methods and techniques emerged to meet the needs of exploring the complex biological system. Metabolomic analysis has been shown to provide useful information in clinical diagnostics of some diseases, such as diabetes mellitus and liver failure [5], [6], [7]. Also, a ¹H-NMR-based metabonomics method has been established for rapid and noninvasive diagnosis of the presence and severity of coronary heart disease [8]. However, metabolic profile and especially lipid metabolic profile analysis were not involved. “Metabolic profile” is a spectrum of the composition and abundance of the metabolites, which can be used to monitor changes over time and in response to particular stimuli [9]. And lipids metabolic profile will contribute to appreciating how lipids react in a biological system and providing a powerful tool for elucidating the mechanism of lipid-based disease, screening novel biomarker, and monitoring clinical pharmacologic therapy [10].

Researchers have developed methodologies to monitor lipid composition in biological samples. Gas chromatography–mass spectrometry (GC–MS) has been a technique widely used for the identification of fatty acids in biological mixtures. Methyl esters are used almost universally for GC analysis of fatty acids [11], [12]. Boron trifluoride (BF₃) in methanol is the most commonly used reagent for the derivatization step [13]. In addition to this method, there have been some reports on direct derivatization methods for the fatty acids in plasma extracts under selective conditions [7], [14]. Recently, several benzylation, silylation and amide reagents were developed for robust and gentle derivatization of fatty acid for GC analysis, such as pentafluorobenzyl (PFB) [15], trimethylsilyl (TMS) [16], tert-butyldimethylsilyl (TBDMS) [17], deoxo-fluor [18] and so on.

The present paper utilize a simple method for comprehensive profiling of fatty acids in human plasma based on GC–MS, and apply to plasma samples of coronary heart disease patients. Metabolic profiles was used to reflect the perturbations of plasma fatty acids of CHD patients with different patterns, and pattern recognition methods were employed such as principal component analysis (PCA) to classify the CHD patients and healthy subjects, and partial least squares-discrimination analysis (PLS-DA) to discriminate two different patterns of CHD in Traditional Chinese Medicine (TCM) clinical practices. We attempted to find out whether different patterns on which TCM always focused might have dissimilar mechanisms in the modern medicine research.