Active matrix metalloproteinases 3 and 9 are independently associated with coronary artery in-stent restenosis

G T Jones1, G P Tarr, L V Phillips

  • 1Vascular Research Group, Section of Surgery, University of Otago, Dunedin, New Zealand. greg.jones@otago.ac.nz

Atherosclerosis
|July 7, 2009
PubMed
Abstract

Insights

Plasma levels of active matrix metalloproteinases (MMP), specifically MMP-3 and MMP-9, predict in-stent restenosis (ISR) after coronary stent placement. Elevated levels of these MMPs significantly increase the risk of ISR development.

Area of Science:

  • Cardiovascular Medicine
  • Biomarker Discovery
  • Interventional Cardiology

Background:

  • In-stent restenosis (ISR) remains a significant complication following coronary stent implantation.
  • Identifying reliable predictors of ISR is crucial for improving patient outcomes and guiding treatment strategies.

Purpose of the Study:

  • To investigate whether plasma levels of active matrix metalloproteinases (MMP) serve as predictors for in-stent restenosis (ISR).
  • To assess the association between specific active MMP isoforms (MMP-1, -2, -3, -9) and ISR in patients receiving bare-metal coronary stents.

Main Methods:

  • A case-control study comparing 152 patients with ISR history to 151 asymptomatic 1-year post-stenting patients (non-ISR).
  • Plasma concentrations of active MMP-1, -2, -3, -9, and TIMP-1 were quantified using sensitive ELISA assays.
  • Demographic and angiographic data were collected for all participants.

Main Results:

  • Active MMP-9 and MMP-3 were independently associated with a history of ISR.
  • Elevated levels of both active MMP-3 and MMP-9 showed a strong association with ISR (OR 11.8, p<0.0001), present in 37% of ISR patients vs. 11% of non-ISR patients.
  • Incorporating MMP biomarkers significantly improved the predictive accuracy (AUC 0.85 vs. 0.78) in ROC analysis.

Conclusions:

  • Plasma levels of active MMP isoforms are significant independent predictors of ISR.
  • Assessing multiple MMP markers demonstrates cumulative utility in predicting ISR, enhancing diagnostic capability.