Literature DB >> 20485748

Untargeted metabolic profiling reveals potential biomarkers in myocardial infarction and its application.

Hong Yao1, Peiying Shi, Ling Zhang, Xiaohui Fan, Qing Shao, Yiyu Cheng.   

Abstract

Although some important biomarkers for myocardial injury have been identified, there still lacks a systematic view of the development and progression of myocardial infarction, including enzymatic regulation, metabolite levels, fluxes, etc., which are pivotal to elucidate the physiological mechanism of disease. Here we present an untargeted analytical approach based on gas chromatography coupled with mass spectrometry (GC-MS) to map the temporal metabolic profilings in blood sera of myocardial infarction rat model prepared by left coronary artery ligation. Using XCMS software (http://metlin.scripps.edu/download/), data processing was simplified greatly. We identified the changes in circulating levels of 24 metabolites during the myocardial ischemia. By combination of previous proteomic results, it gives rise to a new insight view of energy metabolism changes referring to anaerobic glycolysis, citric acid cycle, fatty acid beta-oxidation, and some amino acids metabolism. With these altered metabolism pathways as possible drug targets, we validated a role for the presented metabonomic profiling in the systematic understanding of the action mechanism of component-complex medicine herbs, such as Radix Ophiopogonis, a widely-used anti-myocardial ischemia herbal medicine in Asia.

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Year:  2010        PMID: 20485748     DOI: 10.1039/b925612a

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  9 in total

1.  PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools.

Authors:  Sean O'Callaghan; David P De Souza; Andrew Isaac; Qiao Wang; Luke Hodkinson; Moshe Olshansky; Tim Erwin; Bill Appelbe; Dedreia L Tull; Ute Roessner; Antony Bacic; Malcolm J McConville; Vladimir A Likić
Journal:  BMC Bioinformatics       Date:  2012-05-30       Impact factor: 3.169

2.  Metabolomic signature of arterial stiffness in male patients with peripheral arterial disease.

Authors:  Maksim Zagura; Jaak Kals; Kalle Kilk; Martin Serg; Priit Kampus; Jaan Eha; Ursel Soomets; Mihkel Zilmer
Journal:  Hypertens Res       Date:  2015-07-02       Impact factor: 3.872

3.  Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase.

Authors:  Haitao Lv; Gustavo Palacios; Kirsten Hartil; Irwin J Kurland
Journal:  J Proteome Res       Date:  2011-03-07       Impact factor: 4.466

4.  Tricarboxylic acid cycle related-metabolites and risk of atrial fibrillation and heart failure.

Authors:  Mònica Bulló; Christopher Papandreou; Jesus García-Gavilán; Miguel Ruiz-Canela; Jun Li; Marta Guasch-Ferré; Estefanía Toledo; Clary Clish; Dolores Corella; Ramon Estruch; Emilio Ros; Montserrat Fitó; Chih-Hao Lee; Kerry Pierce; Cristina Razquin; Fernando Arós; Lluís Serra-Majem; Liming Liang; Miguel A Martínez-González; Frank B Hu; Jordi Salas-Salvadó
Journal:  Metabolism       Date:  2021-10-20       Impact factor: 13.934

5.  Exploring the Process of Energy Generation in Pathophysiology by Targeted Metabolomics: Performance of a Simple and Quantitative Method.

Authors:  Marta Riera-Borrull; Esther Rodríguez-Gallego; Anna Hernández-Aguilera; Fedra Luciano; Rosa Ras; Elisabet Cuyàs; Jordi Camps; Antonio Segura-Carretero; Javier A Menendez; Jorge Joven; Salvador Fernández-Arroyo
Journal:  J Am Soc Mass Spectrom       Date:  2015-09-17       Impact factor: 3.109

6.  A Comparative Metabolomics Approach Reveals Early Biomarkers for Metabolic Response to Acute Myocardial Infarction.

Authors:  Sara E Ali; Mohamed A Farag; Paul Holvoet; Rasha S Hanafi; Mohamed Z Gad
Journal:  Sci Rep       Date:  2016-11-08       Impact factor: 4.379

7.  Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis.

Authors:  Xueqin Gao; Chaofu Ke; Haixia Liu; Wei Liu; Kang Li; Bo Yu; Meng Sun
Journal:  Sci Rep       Date:  2017-09-18       Impact factor: 4.379

8.  Ginsenoside Rg1 protects against transient focal cerebral ischemic injury and suppresses its systemic metabolic changes in cerabral injury rats.

Authors:  Mingbao Lin; Wei Sun; Wan Gong; Yasi Ding; Yuanyan Zhuang; Qi Hou
Journal:  Acta Pharm Sin B       Date:  2015-04-08       Impact factor: 11.413

9.  Repetitive transcranial magnetic stimulation applications normalized prefrontal dysfunctions and cognitive-related metabolic profiling in aged mice.

Authors:  Hualong Wang; Yuan Geng; Bing Han; Jing Qiang; Xiaoli Li; Meiyu Sun; Qian Wang; Mingwei Wang
Journal:  PLoS One       Date:  2013-11-22       Impact factor: 3.240

  9 in total

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