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Plasma proteomic analysis of stable coronary artery disease indicates impairment of reverse cholesterol pathway

Trayambak Basak1,2, Vinay Singh Tanwar1, Gourav Bhardwaj1

  • 1Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.

Scientific Reports
|June 29, 2016
PubMed

Insights

Quantitative plasma proteomics identified four key proteins—albumin, Apo A1, Apo C1, and Apo AIV—associated with coronary artery disease (CAD). These proteins, involved in reverse cholesterol transport, significantly improve CAD prediction when combined with traditional risk factors.

Area of Science:

  • Biochemistry
  • Cardiovascular Medicine
  • Proteomics

Background:

  • Coronary artery disease (CAD) is a leading global cause of mortality.
  • Traditional risk factors for CAD have limited predictive accuracy.
  • Quantitative plasma proteomics offers potential for novel biomarker discovery.

Purpose of the Study:

  • To identify differentially expressed proteins in stable CAD patients using a multi-phase approach.
  • To discover novel plasma protein biomarkers for improved CAD risk stratification.
  • To investigate the role of the reverse cholesterol pathway in CAD pathogenesis.

Main Methods:

  • Three-phase study involving discovery, verification, and validation cohorts.
  • iTRAQ-based quantitative proteomic analysis of plasma samples.
  • Multivariate logistic regression and ROC analysis for biomarker association and predictive accuracy.

Main Results:

  • Four proteins—Apolipoprotein A1 (Apo A1), Apolipoprotein A4 (ApoA4), Apolipoprotein C1 (Apo C1), and albumin—were significantly associated with CAD.
  • These proteins, along with diabetes and hypertension, accounted for approximately 88% of CAD cases by ROC analysis.
  • Albumin (OR 6.70) and Apo AI (OR 5.07) showed the strongest association with CAD.

Conclusions:

  • Down-regulation of specific apolipoproteins and albumin suggests impaired reverse cholesterol transport in CAD.
  • The identified proteins represent promising novel biomarkers for CAD.
  • Proteomic approaches can enhance the understanding and prediction of cardiovascular diseases.

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