Cholesterol efflux capacity has been shown to have an inverse relation with coronary artery disease (CAD) and may overcome the limitations of high-density lipoprotein (HDL) cholesterol levels as a predictor for CAD risks. We investigated the predictive value of cholesterol efflux capacity for the prognosis of CAD. Serum cholesterol efflux capacity in 313 patients newly diagnosed with CAD by coronary angiography was measured, and all patients completed a 3-year follow-up. The primary clinical end points were nonfatal myocardial infarction, nonfatal stroke, and cardiovascular mortality. The secondary clinical end points were class IV heart failure requiring hospitalization and coronary artery revascularization. Cholesterol efflux capacity was lower in patients with CAD compared with control group, and decreased cholesterol efflux capacity was associated with an increased risk of acute coronary syndrome (odds ratios, 0.25; 95% confidence interval, 0.14 to 0.46; p <0.01). There was no association between cholesterol efflux capacity and serum HDL cholesterol levels. Follow-up data showed that patients with CAD with lower cholesterol efflux capacity had higher primary clinical end point events (26 of 158 vs 8 of 155, p <0.01). Cox regression and Kaplan-Meier analysis further showed that a decreased cholesterol efflux capacity was associated with an increased risk of the primary end point events regardless of adjustment. There was no association between cholesterol efflux capacity and the secondary end point events. In conclusion, the results provide the important clinical evidence that cholesterol efflux capacity is a predictive index for plaque stability and the prognosis of CAD, independent of HDL cholesterol levels.
The main mechanism underlying high-density lipoprotein (HDL) cholesterol resistance to atherosclerosis is mediating reverse cholesterol transport. In fact, the structure of HDL cholesterol is changing constantly under the effects of a variety of biologically active molecules, from newly living pre-β-HDL to mature α-HDL, in the process of reverse cholesterol transport. Therefore, serum cholesterol efflux capacity (CEC) has been considered as a more promising index of the overall function of different HDL subtypes in the dynamic process of reverse cholesterol transport. Some cross-sectional studies showed that CEC had a strong inverse relation with the likelihood of angiographic coronary artery disease (CAD), independent of HDL cholesterol levels. It is unclear whether CEC has a predictive value for the prognosis of the patients already diagnosed with CAD. We, therefore, investigated the association between CEC and incident cardiovascular outcomes in patients with angiographically confirmed new CAD without taking lipid-lowering medications and prospectively following up these patients.
Methods
Serum samples and associated clinical data were collected from the Department of Cardiology of The First Affiliated Hospital of Anhui Medical University. The study consisted of 313 patients with a primary complaint of angina pectoris who underwent coronary artery angiography from June 2010 to July 2011. Of these, 214 had acute artery syndrome (ACS, including 98 myocardial infarction and 116 unstable angina pectoris) and 99 had stable angina pectoris (SAP). The study also selected patients with angiographically confirmed normal coronary systems as the control group (n = 116). All patients were given written informed consent before study entry, and the study was approved by the local research ethics committee. SAP was defined as typical exertional chest pain brought on by exertion and relieved by rest or sublingual nitrates or with symptoms stable for at least 3 months before study entry. Acute myocardial infarction and unstable angina pectoris were diagnosed using the joint European Society of Cardiology/American College of Cardiology criteria. Coronary artery angiography was performed on all subjects. Images of the coronary tree were obtained with the digital Philips Integris 3000 System (Philips, Eindhoven, Holland) using an automated quantitative coronary artery stenosis assessment process. Two experienced cardiologists who were blind to the patients’ clinical and biochemical data reviewed all the angiographic images to assess the extent of CAD. A diseased coronary artery was defined when the internal diameter decreased by >50%.
The study did not include patients with previously diagnosed CAD or who were receiving treatment by lipid-lowering drugs. Patients with hematologic, renal, liver, or thyroid diseases; excessive alcohol intake; or malignancies were not included in the study. Furthermore, patients with infectious or autoimmune diseases and familial hyperlipidemia and those who underwent surgical procedures in the preceding 3 months were excluded from the study. None of the patients included in the study was receiving anti-inflammatory drugs or hormone replacement therapy.
Blood samples collected from all the participants at baseline (before the follow-up) were placed into ordinary test tubes and stored at 4°C for <4 hours. The blood was then centrifuged, and serum was separated and stored at −80°C. Serum triglyceride (TG), total cholesterol (T-ch), HDL cholesterol, low-density lipoprotein (LDL) cholesterol, apolipoprotein A (Apo A), and apolipoprotein B (Apo B) levels were measured by our biochemistry department using standard methods.
ApoB-depleted serum was prepared by addition of PEG 8000 based on the method previously described by de la Llera-Moya et al. Briefly, 40 parts of 20% PEG 8000 (Sangon Biotech, People’s Republic of China) were added to 100 parts of serum with gentle mixing and then incubated at room temperature for 20 minutes. ApoB-depleted serum was then obtained by recovery of the supernatant after centrifugation (10,000 rpm, 30 minutes, 4°C).
Cholesterol efflux capacity assay was performed as described by Khera et al ; 3 × 10 5 J774 cells, derived from a murine macrophage cell line, plated, and radiolabeled with 2 μCi of 3 H-cholesterol (PerkinElmer, Fremont) per milliliter for 24 hours. ATP-binding cassette transporter, member 1, was upregulated by means of a 16-hour incubation with 0.3 mM 8-(4-chlorophenylthio)-cyclic adenosine monophosphate (Sigma-Aldrich, San Francisco). Subsequently, the efflux medium containing 2.8% Apo B–depleted serum, 2% standard serum (serum control), or without serum (blank control) in MEM-HEPES (0.5 ml per well) was added, respectively, and incubated for 4 hours. All the steps were performed in the presence of acyl-coenzyme A:cholesterol acyl transferase inhibitor Sandoz58-035 (2 μg/ml; Sigma-Aldrich, San Francisco). Liquid scintillation counting was used to quantify the efflux of radioactive cholesterol from the cells. Percent efflux was calculated using the following formula: [microcuries of 3 H-cholesterol in supernatant ÷ (microcuries of 3 H-cholesterol in cells + microcuries of 3 H-cholesterol in supernatant)] × 100. To correct for interassay variation across plates, a pooled serum control from 5 healthy volunteers was included on each plate, and the values of the serum samples from patients were normalized to this pooled value in subsequent analysis. All assays were performed in triplicate.
A follow-up form was designed according to the research purpose and discussed among the team members. The follow-up was performed through telephone by the trained investigators with good communication skills and knowledge on the diagnosis and treatment of CAD. Patients were followed up every 6 months from the day of discharge. The results of the follow-up were entered into the database, a process that was carried out by a designated person and double-checked by an independent person.
The primary clinical end points were composite atherosclerotic cardiovascular disease outcomes, defined as nonfatal myocardial infarction, nonfatal stroke, or cardiovascular mortality. Secondary clinical end points were revascularization, including percutaneous coronary intervention and coronary artery bypass grafting, and class IV heart failure requiring hospitalization.
The results of the normally distributed continuous variables were expressed as the mean value ± SD. The continuous variables with non-normal distributions were presented as the median and interquartile values and were logarithmically transformed as required to approach normal distribution. An analysis of variance was used to evaluate differences among 3 groups or a t test between 2 groups. The qualitative variables presented as frequencies, proportions, and constituent ratios were compared using the chi-square test. Linear regression was used to characterize the relation between CEC and lipid indicators, and non-normal distribution data were first logarithmically transformed as required to approach a normal distribution. A multivariate logistic regression analysis was used to assess the independent adjusted relation between CEC and ACS status. The odds ratios with 95% confidence intervals were calculated for patients with ACS. Cox proportional hazards models and Kaplan-Meier curves were used to assess the association between CEC and clinical end points. Hazard ratios for clinical end points and corresponding 95% confidence intervals were estimated using both unadjusted and adjusted Cox models. A 2-tailed p value <0.05 was considered statistically significant. Statistical analyses were performed using the SPSS software for Windows, version 13.0 (SPSS, Inc., Chicago, Illinois).
Results
In the cross-sectional part of the present study, the baseline clinical characteristics of the patients are listed in Table 1 . There was no significant difference in the clinical characteristics among the 3 groups, with the exception of smoking and serum ApoA levels. Compared with the control and SAP groups, the rate of current smoking in ACS group was higher. The biochemical variables, such as T-ch, TG, LDL cholesterol, HDL cholesterol, and Apo B levels did not differ significantly among the 3 groups. The Apo A levels were lower in the ACS group than in the control and SAP groups. These data suggest that there is a good comparability among the 3 groups.
| Variable | Control (n=116) | SAP (n=99) | ACS (n=214) | p value |
|---|---|---|---|---|
| Age (years) | 65±8 | 66±11 | 67±11 | 0.31 |
| Male | 73% | 70% | 78% | 0. 12 |
| Hypertension | 72% | 70% | 64% | 0.49 |
| Diabetes mellitus | 19% | 24% | 20% | 0.60 |
| Current smoker | 33% | 35% | 50% ∗ | <0.01 |
| T-ch (mmol/L) | 4.45(3.92-5.03) | 4.42(3.74-5.01) | 4. 34(3.57-4.91) | 0.20 |
| TG (mmol/L) | 1.40(1.12-1.89) | 1.49(1.13-2.20) | 1.46(1.09-1.94) | 0.80 |
| HDL cholesterol (mmol/L) | 1.15(0.93-1.32) | 1.11(0.93-1.38) | 1.12(0.90-1.25) | 0.42 |
| LDL cholesterol (mmol/L) | 2.63(2.21-3.11) | 2.61(1.87-3.01) | 2.56(2.02-3.10) | 0.43 |
| Apo A (mmol/L) | 1. 19(1.04-1.40) | 1.18(1.08-1.38) | 1.13(0.97-1.28) ∗ | <0.01 |
| Apo B (mmol/L) | 0.81(0.68-0.90) | 0.82(0.67-0.94) | 0.83(0.70-0.94) | 0.42 |
Figure 1 shows the comparison of serum CEC between SAP and ACS groups that later completed the follow-up. The present study also chose the patients with angiographically confirmed normal coronary as the control group (n = 116). Compared with the control group (2.19 ± 0.88), CEC in SAP (1.55 ± 0.55, p <0.01) and ACS (1.29 ± 0.38, p <0.01) groups was lower. Additionally, ACS group had lower CEC than the SAP group. These data show that CEC is lower in SAP patients and even further reduced in patients with ACS.
As shown in Figure 2 , the multivariate logistic regression analysis showed an inverse correlation between CEC and ACS in patients with CAD. After adjustment for age, gender, traditional cardiovascular risk factors (hypertension, diabetes, current smoking, and serum LDL cholesterol levels), and HDL cholesterol, a decreased CEC was associated with increased relative risk of ACS. These results suggest that a reduced CEC is associated with increased risk of developing ACS.
Association between CEC and serum lipids indexes was investigated in patients with CAD. Table 2 lists that there was no linear association between CEC and serum levels of T-ch, TG, LDL cholesterol, and HDL cholesterol or the Apo B levels. CEC had a weak positive correlation with serum Apo A levels (shown in Figure 3 ). These observations suggest that CEC is a distinctive index for CAD risks, which may not be reflected by the conventional indexes of serum lipid levels.
| Lipid | r value | p value |
|---|---|---|
| T-ch (mmol/L) | 0.05 | 0.84 |
| TG (mmol/L) | 0.07 | 0.53 |
| LDL cholesterol (mmol/L) | 0.01 | 0.96 |
| HDL cholesterol (mmol/L) | -0.09 | 0.26 |
| ApoB (mmol/L) | -0.03 | 0.85 |
| ApoA (mmol/L) | 0.30 | <0.01 |
In the prospective follow-up part of the present study, 313 patients with CAD completed 3 years of follow-up. Patients were divided into 2 groups according to the median CEC (1.30). The clinical data of these 2 groups are listed in Table 3 . There was no significant difference in age, gender, hypertension, diabetes, current smoking, serum levels of lipids (T-ch, TG, HDL cholesterol, and LDL cholesterol), and Apo B between the 2 groups. The levels of Apo A were higher in the CEC >1.30 group. There was no significant difference in regular medication between the 2 groups. These data show that the clinical data at the entry time point between high and low CEC groups were largely comparable.
| Variable | All Patients (n=313) | CEC≤1.30 (n=158) | CEC>1.30 (n=155) | p value |
|---|---|---|---|---|
| Age (years) | 67±11 | 67±11 | 66±11 | 0.61 |
| Male sex | 75% | 75% | 75% | 0. 92 |
| Hypertension | 66% | 69% | 63% | 0.23 |
| Diabetes mellitus | 21% | 24% | 19% | 0.25 |
| Current smoker | 46% | 46% | 45% | 0.85 |
| T-ch (mmol/L) | 4.38(3.62-4.95) | 4.25(3.58-4.79) | 4. 42(3.80-5.08) | 0.07 |
| TG (mmol/L) | 1.46(1.10-2.01) | 1.45(1.07-1.94) | 1.48(1.13-2.18) | 0.47 |
| HDL cholesterol (mmol/L) | 1.12(0.90-1.29) | 1.10(0.87-1.26) | 1.12(0.93-1.29) | 0.39 |
| LDL cholesterol (mmol/L) | 2.60(1.99-3.04) | 2.51(1.92-2.99) | 2.61(2.00-3.10) | 0.08 |
| Apo A (mmol/L) | 1. 17(1.00-1.31) | 1.11(0.94-1.24) | 1.18(1.08-1.38) | <0.01 |
| Apo B (mmol/L) | 0.83(0.69-0.94) | 0.82(0.68-0.90) | 0.83(0.69-0.99) | 0.26 |
| Regular medication | 21% | 22% | 21% | 0.85 |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
