Coronary Plaque Characteristics Assessed by Optical Coherence Tomography and Plasma Lipoprotein(a) Levels in Patients With Acute Coronary Syndrome.

Abstract

Background: Lipoprotein(a) [Lp(a)] is associated with increased cardiovascular risk, but its influence on plaque characteristics at optical coherence tomography (OCT) evaluation is not fully understood.

Aims: This study seeks to explore the impact of Lp(a) levels on plaque morphology as assessed by OCT in a very high-risk subset of patients.

Methods: Consecutive patients admitted for acute coronary syndrome (ACS) and undergoing OCT-guided percutaneous coronary intervention (PCI) at a large tertiary care center between 2019 and 2022 were deemed eligible for the current analysis. The overall population was categorized into two subgroups according to baseline Lp(a) levels: (1) lower Lp(a) (Lp(a) ≤ 300 mg/L) and (2) elevated Lp(a) (Lp(a)  $\ge$  300 mg/L). Predictors of lipid-rich plaques were identified using multivariable logistic regression with stepwise selection of candidate covariates.

Results: A total of 202 patients were included in this study. OCT findings revealed that patients with elevated Lp(a) had a higher prevalence of lipid-rich plaques, a significantly greater mean lipid arc, along with increased macrophage infiltration and thin-cap fibroatheroma (TCFA). In contrast, calcific plaque prevalence was higher in the lower Lp(a) group. Multivariable regression analysis identified low-density lipoprotein cholesterol ≥ 70 mg/dL, and elevated Lp(a) as strong predictors of lipid-rich plaques at OCT.

Conclusion: In this observational study including ACS patients undergoing OCT-guided PCI, those with elevated Lp(a) levels exhibited a higher prevalence of lipid-rich plaques, increased macrophage infiltration, and TCFA, thereby indicating a more vulnerable plaque phenotype. Additionally, elevated Lp(a) levels and LDL-C levels ≥ 70 mg/dL were each independently associated with lipid enrichment of coronary plaques. These findings suggest Lp(a), beyond other well-known risk factors, as a key marker for risk stratification, potentially informing optimal medical management strategies.