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Journal of Vascular Surgery: Venous and Lymphatic Disorders 2016-Apr

1D-¹H-nuclear magnetic resonance metabolomics reveals age-related changes in metabolites associated with experimental venous thrombosis.

केवल पंजीकृत उपयोगकर्ता ही लेखों का अनुवाद कर सकते हैं
साइन अप करने के लिए लॉग इन करें
लिंक क्लिपबोर्ड पर सहेजा गया है
Andrea T Obi
Kathleen A Stringer
Jose A Diaz
Michael A Finkel
Diana M Farris
Larisa Yeomans
Thomas Wakefield
Daniel D Myers

कीवर्ड

सार

OBJECTIVE

Age is a significant risk factor for the development of venous thrombosis (VT), but the mechanism(s) that underlie this risk remain(s) undefined and poorly understood. Aging is known to adversely influence inflammation and affect metabolism. Untargeted metabolomics permits an agnostic assessment of the physiological landscape and lends insight into the mechanistic underpinnings of clinical phenotypes. The objective of this exploratory study was to test the feasibility of a metabolomics approach for identifying potential metabolic mechanisms of age-related VT.

METHODS

We subjected whole blood samples collected from young and old nonthrombosed controls and VT mice 2 days after thrombus induction using the electrolytic inferior vena cava, to a methanol:chloroform extraction and assayed the resulting aqueous fractions using 1D-(1)H- nuclear magnetic resonance. Normalized mouse metabolite data were compared across groups using analysis of variance (ANOVA) with Holm-Sidak post-testing. In addition, associations between metabolite concentrations and parameters of thrombosis such as thrombus and vein wall weights, and markers of inflammation, vein wall P- and E-selectin levels, were assessed using linear regression. The relatedness of the found significant metabolites was visually assessed using a bioinformatics tool, Metscape, which generates compound-reaction-enzyme-gene networks to aid in the interpretation of metabolomics data.

RESULTS

Old mice with VT had a greater mean vein wall weight compared with young mice with VT (P < .05). Clot weight differences between old and young mice followed the same trend as vein wall weight (0.011 ± 0.04 g vs 0.008 ± 0.003 g; P = not significant). Glutamine (ANOVA, P < .01), proline (ANOVA, P < .01), and phenylalanine (ANOVA, P < .05) levels were increased in old VT mice compared with age-matched controls and young VT mice. Betaine and/or trimethylamine N-oxide levels were increased in aged mice compared with young animals. Vein wall weight was strongly associated with glutamine (P < .05), and phenylalanine (P < .01) concentrations and there was a trend toward an association with proline (P = .09) concentration. Vein wall P-selectin, but not E-selectin levels, were increased in old VT mice and were associated with the three found metabolites of age-related VT. Collectively, with the addition of glutamate, these metabolites form a single compound-reaction-enzyme-gene network that was generated by Metscape.

CONCLUSIONS

We used 1D-(1)H-nuclear magnetic resonance-metabolite profiling to identify, for the first time, in an experimental model, three potential metabolites, glutamine, phenylalanine, and proline, associated with age-related VT. These metabolites are metabolically related and their levels are associated with vein wall weight and P-selectin concentrations. In aggregate, these findings provide a "roadmap" of pathways that could be interrogated in future studies, which could include provocation of the glutamine, phenylalanine, and proline pathways in the vein wall. This study introduces metabolomics as a new approach to furthering knowledge about the mechanisms of age-related VT.

हमारे फेसबुक पेज से जुड़ें

विज्ञान द्वारा समर्थित सबसे पूर्ण औषधीय जड़ी बूटी डेटाबेस

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  • इंटरएक्टिव जीपीएस नक्शा - स्थान पर टैग जड़ी बूटियों (जल्द ही आ रहा है)
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