Literature DB >> 28341595

Systems characterization of differential plasma metabolome perturbations following thrombotic and non-thrombotic myocardial infarction.

Patrick J Trainor1, Bradford G Hill1, Samantha M Carlisle2, Eric C Rouchka3, Shesh N Rai4, Aruni Bhatnagar1, Andrew P DeFilippis5.   

Abstract

Myocardial infarction (MI) is an acute event characterized by myocardial necrosis. Thrombotic MI is caused by spontaneous atherosclerotic plaque disruption that results in a coronary thrombus; non-thrombotic MI occurs secondary to oxygen supply-demand mismatch. We sought to characterize the differential metabolic perturbations associated with these subtypes utilizing a systems approach. Subjects presenting with thrombotic MI, non-thrombotic MI and stable coronary artery disease (CAD) were included. Whole blood was collected at two acute time-points and at a time-point representing the quiescent stable disease state. Plasma metabolites were analyzed by untargeted UPLC-MS/MS and GC-MS. A weighted network was constructed, and modules were determined from the resulting topology. To determine perturbed modules, an enrichment analysis for metabolites that demonstrated between-group differences in temporal change across the disease state transition was then conducted. BIOLOGICAL SIGNIFICANCE: We report evidence of metabolic perturbations of acute MI and determine perturbations specific to thrombotic MI. Specifically, a module characterized by elevated glucocorticoid steroid metabolites following acute MI showed greatest perturbation following thrombotic MI. Modules characterized by elevated pregnenolone metabolites, monoacylglycerols, and acylcarnitines were perturbed following acute MI. A module characterized by a decrease in plasma amino acids following thrombotic MI was differentially perturbed between MI subtypes.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Coronary artery disease; Metabolomics; Myocardial infarction; Network analysis; Systems biology

Mesh:

Substances:

Year:  2017        PMID: 28341595      PMCID: PMC5496773          DOI: 10.1016/j.jprot.2017.03.014

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  32 in total

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