Relationship of atherosclerotic lesion by optical coherence tomography with cholesterol efflux capacity by immobilized liposome-bound gel beads method

Scritto il 10/04/2026
da Tsunehiro Miyakoshi

Atherosclerosis. 2026 Apr 2:120724. doi: 10.1016/j.atherosclerosis.2026.120724. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Cholesterol efflux capacity (CEC) is robust biomarker for atherosclerotic cardiovascular disease (ASCVD). However, cell-based CEC assays require complex procedures that limit clinical use. The immobilized liposome-bound gel beads (ILG) method, a newly developed cell-free CEC assay, demonstrates sufficient performance for clinical application. This study investigated the clinical significance of CEC measured by the ILG method in relation to HDL subclasses and coronary artery plaque characteristics.

METHODS: We analyzed CEC and HDL parameters, including the ratio of apolipoprotein E (apoE)-HDL-C to HDL-C (%apoE) and HDL3-C/HDL2-C, in 61 patients who underwent coronary angiography or percutaneous coronary intervention. Coronary artery plaques were assessed by optical coherence tomography (OCT). A large lipid-rich plaque was defined as lipid length >5 mm and lipid arc >180°.

RESULTS: CEC correlated positively with HDL-C and %apoE. Among the patients, 26 (42.6%) exhibited large lipid-rich plaques on OCT. Univariable analysis showed that CEC was significantly lower in patients with large lipid-rich plaques compared to those without. While this association did not reach statistical significance after multivariable adjustment (p = 0.109), the addition of CEC to traditional risk factors improved the model's explanatory power (Nagelkerke R2: 0.346 to 0.381) and discriminatory ability (AUC: 0.775 to 0.805) for large lipid-rich plaques.

CONCLUSIONS: CEC measured using the ILG method reflects HDL subclass features and is associated with the burden of lipid-rich coronary artery plaques. These findings suggest the significance of CEC evaluated using the ILG method, supporting its potential for enhanced ASCVD risk assessment and further clinical applications.

PMID:41963144 | DOI:10.1016/j.atherosclerosis.2026.120724