title: Metabolic Phenotypes of Carotid Atherosclerotic Plaques Relate to Stroke Risk: An Exploratory Study.
abstract: Stroke is a major cause of death and disability. That three-quarters of stroke patients will never have previously manifested cerebrovascular symptoms demonstrates the unmet clinical need for new biomarkers able to stratify patient risk and elucidation of the biological dysregulations. In this study, the utility of comprehensive metabolic phenotyping is assessed to provide candidate biomarkers that relate to stroke risk in stenosing carotid plaque tissue samples.
  
  
  
  Carotid plaque tissue samples were obtained from patients with cerebrovascular symptoms of carotid origin (n = 5), and from asymptomatic patients (n = 5). Two adjacent biological replicates were obtained from each tissue. Organic and aqueous metabolite extracts were obtained separately and analysed using two ultra performance liquid chromatography coupled to mass spectrometry metabolic profiling methods. Multivariate and univariate tools were used for statistical analysis.
  
  
  
  The two study groups demonstrated distinct plaque phenotypes using multivariate data analysis. Univariate statistics also revealed metabolites that differentiated the two groups with a strong statistical significance (p = 10(-4)-10(-5)). Specifically, metabolites related to the eicosanoid pathway (arachidonic acid and arachidonic acid precursors), and three acylcarnitine species (butyrylcarnitine, hexanoylcarnitine, and palmitoylcarnitine), intermediates of the β-oxidation, were detected in higher intensities in symptomatic patients. However, metabolites implicated in the process of cell death, a process known to be upregulated in the formation of the vulnerable plaque, were unaffected.
  
  
  
  Discrimination between symptomatic and asymptomatic carotid plaque tissue is demonstrated for the first time using metabolic profiling technologies. Two biological pathways (eicosanoid and β-oxidation) were implicated in differentiating symptomatic from asymptomatic patients and will be further investigated. These results indicate that metabolic phenotyping should be further explored to investigate the chemistry of the unstable plaque, in the pursuit of candidate biomarkers for risk-stratification and targets for pharmacotherapeutic intervention.
authors.affiliation: Section of Biomolecular Medicine, Division of Computational & Systems Medicine, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK.
authors.forename: P A
authors.initials: PA
authors.lastname: Vorkas
authors.affiliation: Academic Section of Vascular Surgery, Division of Surgery, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK.
authors.forename: J
authors.initials: J
authors.lastname: Shalhoub
authors.affiliation: Section of Biomolecular Medicine, Division of Computational & Systems Medicine, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK.
authors.forename: M R
authors.initials: MR
authors.lastname: Lewis
authors.affiliation: Section of Biomolecular Medicine, Division of Computational & Systems Medicine, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK.
authors.forename: K
authors.initials: K
authors.lastname: Spagou
authors.affiliation: Section of Biomolecular Medicine, Division of Computational & Systems Medicine, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK.
authors.forename: E J
authors.initials: EJ
authors.lastname: Want
authors.affiliation: Section of Biomolecular Medicine, Division of Computational & Systems Medicine, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK.
authors.forename: J K
authors.initials: JK
authors.lastname: Nicholson
authors.affiliation: Academic Section of Vascular Surgery, Division of Surgery, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK.
authors.forename: A H
authors.initials: AH
authors.lastname: Davies
authors.affiliation: Section of Biomolecular Medicine, Division of Computational & Systems Medicine, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, UK. Electronic address: elaine.holmes@imperial.ac.uk.
authors.forename: E
authors.initials: E
authors.lastname: Holmes
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016718:Arachidonic Acid / Q000032:analysis / Q000378:metabolism; D015415:Biomarkers / Q000737:chemistry; D002331:Carnitine / Q000031:analogs & derivatives / Q000737:chemistry; D016893:Carotid Stenosis / Q000150:complications / Q000378:metabolism*; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D055432:Metabolomics; D008875:Middle Aged; D010172:Palmitoylcarnitine / Q000737:chemistry; D010641:Phenotype; D058226:Plaque, Atherosclerotic / Q000737:chemistry; D012307:Risk Factors; D020521:Stroke / Q000209:etiology* / Q000378:metabolism
chemical_list: D015415:Biomarkers; C061301:hexanoylcarnitine; D010172:Palmitoylcarnitine; C427065:butyrylcarnitine; D016718:Arachidonic Acid; D002331:Carnitine
keywords: Embolic stroke; Lipid profiling; Lipidomics; Mass spectrometry; Metabolic phenotyping; Metabolic profiling; Metabolomics; Metabonomics