Identification of metabolic markers in coronary artery disease using an untargeted LC-MS based metabolomic approach

Coronary artery disease (CAD), a complex metabolic disorder, is one of the largest causes of death worldwide. Both environmental and genetic factors contribute to the etiology of this metabolic disease. The gene-environment interaction could lead to modulation of various metabolic pathways resulting in altered levels of various metabolites. Thus, identifying metabolites could aid in deciphering pathways that could be involved in the pathophysiology of the disease. With the advent of high resolution mass spectrometry based methodologies, it is now possible to screen thousands of metabolites in a single snapshot thus, allowing the identification of potential disease metabolite markers. In this work, using an untargeted metabolomic approach, we attempted to identify metabolites that have altered levels in CAD patients. Using reverse phase and HILIC based chromatography followed by mass spectrometry we identified a total of 32 metabolites (2 fold; p<0.05) in plasma whose levels were significantly altered in CAD samples. Further, we have validated the discriminative ability of these metabolites in an independent set of CAD and control samples using multivariate PLS-DA analysis. Interestingly, Lyso PC (18:0), Cortisol, Lyso PC (P-17:0), and glycerophosphocholine were among the top discriminators for CAD which implies involvement of phosphatidylcholine pathway in the pathogenesis of atherosclerosis.

Herein, we report that an unbiased metabolomic study has the potential to identify newer markers which are involved in several important biological pathways like lipid metabolism, phosphatidylcholine pathway etc. which in turn are implicated in CAD. These markers could be of potential clinical importance for screening subjects at risk of CAD. This article is part of a Special Issue entitled: Proteomics in India.