HDL-C is a Marker of Coronary Artery Disease Severity and Inflammation in Patients on Statin Therapy.

Cardiovasc Revasc Med

Inova Center for Thrombosis Research and Drug Development, Inova Heart and Vascular Institute, Falls Church FVA, USA. Electronic address:

Published: November 2019

Introduction: Low high-density lipoprotein (HDL-C) and inflammation are risk factors for coronary artery disease (CAD). However, limited data are available determining the role of HDL-C sub-particles HDL-C and HDL-C for assessing CAD severity in patients on statin therapy.

Methods: Blood samples were obtained prior to cardiac catheterization in 304 consecutive patients with suspected CAD on statin therapy in this sub-analysis of Multi-Analyte, thrombogenic, and Genetic Markers of Atherosclerosis (MAGMA, NCT01276678) study. Detailed lipid profiling and oxidized LDL (ox-LDL) were analyzed. CAD severity was angiographically defined as severe CAD (>75% luminal diameter stenosis [LDS]) and non-severe CAD (≤75% LDS). Multi-regression analysis was performed to test for statistical significance. Receiver operator curve (ROC) analysis was performed to determine cut-point for predicting severe CAD.

Results: Patients with severe CAD had a significantly lower total-HDL-C, lower HDL-C and higher lipoprotein(a) levels. HDL-C and lipoprotein(a) cholesterol [Lp(a)-C] retained statistical significance on multiple regression analysis. ROC analysis showed HDL-C to have a C-statistic of 0.60 (p = 0.003) and Lp(a)-C to have a C-statistic of 0.61 (p = 0.0007). Patients with HDL-C ≤ 33 mg/dL and Lp(a)-C > 7 mg/dL were found to have significantly elevated ox-LDL levels.

Conclusion: In patients on statin therapy, HDL-C and Lp(a)-C improve prediction of severe CAD compared to a traditional lipid panel. In addition, patients with HDL-C ≤ 33 mg/dL and Lp(a)-C > 7 mg/dL have greater inflammation marked by ox-LDL. Further studies are needed to evaluate the utility of these novel biomarkers in predicting CAD severity.

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Source
http://dx.doi.org/10.1016/j.carrev.2018.12.019DOI Listing

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