Small Dense LDL Level and LDL/HDL Distribution in Acute Coronary Syndrome Patients

Abstract

This study aimed to determine the size and distribution of LDL and HDL particles in North African acute coronary syndrome (ACS) patients and to compare the level of small dense LDL (sdLDL) to other markers used in cardiovascular risk prediction.

Methods: A total of 205 ACS patients and 100 healthy control subjects were enrolled. LDL particle size and LDL and HDL subclass distributions were measured using Quantimetric Lipoprint^® linear polyacrylamide gel electrophoresis. Lipid ratios (total cholesterol, LDL cholesterol, non-HDL cholesterol, and HDL cholesterol) were determined to calculate the atherogenic index of plasma (AIP), the atherogenic coefficient (AC), Castelli's Risk-I (CR-I), and Castelli's Risk-II (CR-II). Receiver operating characteristic (ROC) curve analyses and area under the curve (AUC) were used to assess the predictive value of sdLDL as a marker for cardiovascular disease.

Results: The ACS patients, compared to the healthy control subjects, displayed an alteration of LDL particle distribution, with a significant increase in sdLDL serum concentrations (0.303 ± 0.478 mmol/L vs. 0.0225 ± 0.043 mmol/L, respectively, p < 0.001). The sdLDL levels had a high discrimination accuracy [AUC = 0.847 ± 0.0353 (95% CI 0.778 to 0.916, p < 0.0001)]. The best predictive cutoff value of ACS determined with the maximum Youden index (J) [(sensitivity + specificity) - 1 = 0.60] was 0.038 mmol/L. A Spearman correlation analysis showed that sdLDL levels were moderately but significantly and positively correlated with AC and CR-I (r = 0.37, p < 0.001) and weakly but significantly correlated with PAI and CR-II; r = 0.32 (p < 0.001) and r = 0.30 (p < 0.008), respectively. The subclass distribution of HDL particles from ACS patients was also altered, with a decrease in large HDL particles and an increase in small HDL particles compared to HDL from healthy control subjects.

Conclusion: Due to their high atherogenicity, sdLDL levels could be used as a valuable marker for the prediction cardiovascular events.

Keywords: LDL and HDL subclass distribution; ROC curve; acute coronary syndrome; sdLDL.

Figure 1

Subclass distribution profile of LDL using the Quantimetrix^® Lipoprint^® LDL System. EDTA-plasma samples were used for the LDL particles size analysis. LDL were separated into seven fractions (LDL1 to LDL7), of which fractions 1 and 2 corresponded to large buoyant LDL (lbLDL) and fractions 3 to 7 corresponded to small dense LDL (sdLDL). LDL were obtained from healthy control subjects (A) and from ACS patients (B). Subclass distribution is presented in concentration of cholesterol (mg/dL) and in % (area %). Particle size is expressed in angstroms (Å).

Figure 2

(A) Lipoprotein subclass distribution of LDL from ACS patients compared to healthy control subjects. (B) Measurement of sdLDL-forming LDL obtained from ACS patients compared to healthy control subjects. (C) Measurement of sdLDL-forming LDL obtained from non-smoker and smoker ACS patients compared to healthy (non-smoker) control subjects. LDL subclass distribution analysis and sdLDL quantification were determined using the Quantimetrix^® Lipoprint^® LDL System.**** p < 0.0001 *** p < 0.0003 and * p < 0.01.

Figure 3

Receiver operating characteristic (ROC) curves exhibiting the discriminatory power of sdLDL. C*: optimum cutoff value of ACS determined using the maximum Youden index (J) [(sensitivity + specificity) − 1 = 0.60].

Figure 4

Receiver operating characteristic (ROC) curves showing the discriminatory power of sdLDL, AIP, AC, CR-I, and CRII.

Figure 5

Lipoprotein subclass distribution of HDL from ACS patients compared to healthy control subjects. HDL subclass distribution analysis was determined using the Quantimetrix^® Lipoprint^® HDL System. *** p < 0.0003 and * p < 0.01.