International Journal of Cardiology. Cardiovascular Risk and Prevention (Sep 2025)

Circulating protein biomarkers and their association with vulnerable plaque characteristics – a PROSPECT II substudy

  • Tania Sharma,
  • Akiko Maehara,
  • Michael Maeng,
  • Lars Kjøller-Hansen,
  • Thomas Engstrøm,
  • Ori Ben-Yehuda,
  • Mitsuaki Matsumura,
  • Ole Fröbert,
  • Jonas Persson,
  • Rune Wiseth,
  • Alf Inge Larsen,
  • Sasha Koul,
  • Rebecca Rylance,
  • Gary S. Mintz,
  • Ziad A. Ali,
  • Stefan K. James,
  • Gregg W. Stone,
  • David Erlinge

DOI
https://doi.org/10.1016/j.ijcrp.2025.200440
Journal volume & issue
Vol. 26
p. 200440

Abstract

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Background: In the PROSPECT-II study, near infrared spectroscopy (NIRS) and intravascular ultrasound (IVUS) was used to characterize atherosclerotic plaques in the coronary arteries. NIRS-derived lipid core burden index (LCBI) and IVUS-derived plaque burden (PB) were able to identify plaques strongly associated with adverse cardiovascular events. Aim: Our aim was to identify biomarkers associated with LCBI or PB in the coronary arteries. Methods: 898 patients with recent myocardial infarction underwent percutaneous coronary intervention. Blood samples to analyze plasma levels of 179 proteins associated with cardiovascular disease were procured and a combined NIRS-IVUS catheter was used to analyze the coronary arteries. Adjusted linear regression models were calculated between the biomarkers and the outcomes of interest, adjusted for multiplicity testing. Kaplan-Meier survival curves of biomarkers divided by median were assessed with the log-rank test. Adjusted Cox proportional models were calculated for major adverse cardiovascular events. Results: A total of 24 proteins were associated with PB and 28 proteins with LCBI. Eight of these biomarkers were associated with both increased pan-coronary LCBI and PB; IL-18R1, CSF-1, VEGFA, EN-RAGE, cathepsin D, PCSK9, transferrin receptor protein 1 and OPN. After adjusting for multiplicity, angiopoietin like 3 (ANGPTL3) retained its association with LCBI, and IL-18R1 and CSF-1 retained their association with PB. Conclusion: We were able to identify distinct biomarker patterns associated with PB and LCBI. IL-18R1 and CSF-1 had a strong relationship with PB. ANGPTL3 was associated with lipid rich plaques but not with PB, supporting its role in lipid accumulation and development of vulnerable plaques.

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