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Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics.

Publication ,  Journal Article
Jing, L; Parker, CE; Seo, D; Hines, MW; Dicheva, N; Yu, Y; Schwinn, D; Ginsburg, GS; Chen, X
Published in: Proteomics
July 2011

Due to the lack of precise markers indicative of its occurrence and progression, coronary artery disease (CAD), the most common type of heart diseases, is currently associated with high mortality in the United States. To systemically identify novel protein biomarkers associated with CAD progression for early diagnosis and possible therapeutic intervention, we employed an iTRAQ-based quantitative proteomic approach to analyze the proteome changes in the plasma collected from a pair of wild-type versus apolipoprotein E knockout (APOE(-/-) ) mice which were fed with a high fat diet. In a multiplex manner, iTRAQ serves as the quantitative 'in-spectra' marker for 'cross-sample' comparisons to determine the differentially expressed/secreted proteins caused by APOE knock-out. To obtain the most comprehensive proteomic data sets from this CAD-associated mouse model, we applied both MALDI and ESI-based mass spectrometric (MS) platforms coupled with two different schemes of multidimensional liquid chromatography (2-D LC) separation. We then comparatively analyzed a series of the plasma samples collected at 6 and 12 wk of age after the mice were fed with fat diets, where the 6- or 12-wk time point represents the early or intermediate phase of the fat-induced CAD, respectively. We then categorized those proteins showing abundance changes in accordance with APOE depletion. Several proteins such as the γ and β chains of fibrinogen, apolipoprotein B, apolipoprotein C-I, and thrombospondin-4 were among the previously known CAD markers identified by other methods. Our results suggested that these unbiased proteomic methods are both feasible and a practical means of discovering potential biomarkers associated with CAD progression.

Duke Scholars

Published In

Proteomics

DOI

EISSN

1615-9861

Publication Date

July 2011

Volume

11

Issue

14

Start / End Page

2763 / 2776

Location

Germany

Related Subject Headings

  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
  • Proteomics
  • Mice, Knockout
  • Mice, Inbred C57BL
  • Mice
  • Male
  • Humans
  • Female
  • Disease Progression
  • Coronary Artery Disease
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Jing, L., Parker, C. E., Seo, D., Hines, M. W., Dicheva, N., Yu, Y., … Chen, X. (2011). Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics. Proteomics, 11(14), 2763–2776. https://doi.org/10.1002/pmic.201000202
Jing, Linhong, Carol E. Parker, David Seo, Maria Warren Hines, Nedyalka Dicheva, Yanbao Yu, Debra Schwinn, Geoffrey S. Ginsburg, and Xian Chen. “Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics.Proteomics 11, no. 14 (July 2011): 2763–76. https://doi.org/10.1002/pmic.201000202.
Jing, Linhong, et al. “Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics.Proteomics, vol. 11, no. 14, July 2011, pp. 2763–76. Pubmed, doi:10.1002/pmic.201000202.
Jing L, Parker CE, Seo D, Hines MW, Dicheva N, Yu Y, Schwinn D, Ginsburg GS, Chen X. Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics. Proteomics. 2011 Jul;11(14):2763–2776.
Journal cover image

Published In

Proteomics

DOI

EISSN

1615-9861

Publication Date

July 2011

Volume

11

Issue

14

Start / End Page

2763 / 2776

Location

Germany

Related Subject Headings

  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
  • Proteomics
  • Mice, Knockout
  • Mice, Inbred C57BL
  • Mice
  • Male
  • Humans
  • Female
  • Disease Progression
  • Coronary Artery Disease