Serum protein profiles predict coronary artery disease in symptomatic patients referred for coronary angiography

William A LaFramboise1, Rajiv Dhir, Lori A Kelly

  • 1University of Pittsburgh, Department of Pathology, 5230 Centre Avenue, Pittsburgh, PA 15232, USA. laframboisewa@upmc.edu

BMC Medicine
|December 11, 2012
PubMed

Insights

A novel multiplex serum protein test can identify patients without significant coronary artery disease (CAD), reducing the need for invasive cardiac catheterization. This biomarker approach offers a low-risk, cost-effective alternative for diagnosing CAD.

Area of Science:

  • Cardiovascular Medicine
  • Biomarker Discovery
  • Diagnostic Testing

Background:

  • Millions of cardiac catheterizations are performed annually in the US.
  • Nearly half of these procedures reveal no significant coronary artery disease (CAD).
  • A low-risk, cost-effective diagnostic test is needed to rule out CAD.

Purpose of the Study:

  • To identify serum protein biomarkers for diagnosing coronary artery disease (CAD).
  • To develop a multiplex protein test to reduce unnecessary cardiac catheterizations.

Main Methods:

  • Analyzed serum proteins in 359 symptomatic patients undergoing catheterization.
  • Compared protein levels between patients with and without significant CAD.
  • Developed and validated protein signatures using machine learning.

Main Results:

  • Identified significant differences in circulating proteins between patients requiring revascularization and those without.
  • Developed 14 overlapping protein signatures with 95% sensitivity for detecting significant CAD.
  • Key biomarkers included osteopontin, resistin, and C-reactive protein (CRP).

Conclusions:

  • Serum protein profiles reflect inflammatory response and lipid metabolism alterations in CAD patients.
  • A targeted multiplex serum protein test can identify patients without significant CAD.
  • This approach can eliminate radiation exposure and reduce healthcare costs associated with angiographic testing.
Abstract

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