Institute of Microcirculation, Peking Union Medical College & Chinese Academy of Medical Sciences, Key Lab of Microcirculation, National Health and Family Planning Commission, China
Received Date: July 07, 2014; Accepted Date: July 28, 2014; Published Date: August 03, 2014
Citation: Hu SS, Zhang HG, Zhang QJ, Xiu RJ (2014) Increased Circulating Apoptotic CD31+/CD42b- and Activated CD62E+ Endothelial Micro Particles in Coronary Artery Disease. J Hypertens 3:167. doi:10.4172/2167-1095.1000167
Copyright: © 2014 Hu SS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Objective: To examine the phenotypes of endothelial microparticles and platelet microparticles in order to identify a sensitive endothelial microparticle biomarker for monitoring endothelial dysfunction in patients with coronary artery disease, and to examine the mechanisms underlying endothelial dysfunction.
Methods: Thirty-three coronary artery disease patients and 53 healthy subjects were recruited. The absolute numbers of endothelial microparticles and platelet microparticles were measured by flow cytometry, and the clinical characteristics of patients and healthy subjects were recorded. Spearman’s correlation analysis and multiple linear regression analysis were performed to analyse the correlation between endothelial microparticles and platelet microparticles, and between microparticles and clinical data.
Results: There was a significant difference in the number of CD31+/CD42b- endothelial microparticles and CD62E+ endotheial microparticles between patients with coronary artery diease and healthy subjects (p<0.05).
Conclusion: Both endothelial apoptosis and activation play an important role in coronary artery disease, although endothelial apoptosis plays the major role. Endothelial microparticles may be used to monitor endothelial dyfunction in patients with coronary artery disease.
Endothelial dysfunction; Endothelial microparticles; Coronary artery disease
Endothelial Dysfunction (ED) is an important pathophysiological mechanism that underlies the development of Coronary Artery Disease (CAD) . ED is also predictive of prognosis and cardiovascular risk . Therefore, it is important to identify new biomarkers that can be used to monitor ED in CAD and to identify the underlying mechanisms. ED is determined by the balance between endothelial activation and endothelial apoptosis. Endothelial Microparticles (EMP) are derived from endothelial cells in response to endothelial activation and apoptosis. Some studies report that CD31+EMP are shed from apoptotic endothelial cells, whereas CD62E+ EMP are shed by activated endothelial cells . In addition, a previous study reported that the levels of EMP are higher in CAD patients than in healthy controls . Therefore, the aims of the present study were to examine the phenotypes of EMP and Platelet Microparticles (PMP) in order to identify a sensitive endothelial microparticle biomarker for monitoring ED in CAD, and to examine the mechanisms underlying ED.
Clinical study population
Thirty-three CAD patients and 53 healthy subjects were enrolled. CAD was diagnosed when stenosis (≥ 50% of the lumen diameter) was detected in a major coronary artery (the left main coronary artery, the left anterior descending artery, the left circumflex artery, or the right coronary artery) by coronary arteriography. Patients with a history of inflammatory, chronic renal failure, hepatic or hematologic disorders, or autoimmune or malignant diseases were excluded. Healthy subjects were included if they had no known history of medical illness and a normal physical examination. The study protocol was approved by the Institutional Review Boards and Ethics Committees of the Microcirculation Peking Union Medical College and Chinese Academy of Medical Science. All patients and controls provided verbal informed consent before entering the study.
Isolation and measurement of microparticles
Blood was drawn into blue-top vacuum tubes containing sodium citrate. Within 1 hour, whole blood (3 ml per sample) was centrifuged at 1500×g for 10 min to prepare platelet-rich plasma and then again for 10 min at 13,000×g to obtain platelet-poor plasma. The plasma products were stored at -20°C for 1 week and then at -80°C until analysis. A single thaw cycle did not affect microparticle levels in the plasma.
For the EMP assay, platelet-poor plasma (50 μl) was incubated with the following monoclonal antibodies (4 μl of each): phycoerythrin (PE)-labeled anti-CD31 (560983; BD Biosciences), PE-anti-CD62E (551145; BD Biosciences), PE-anti-CD144 (VE-Cadherin, 12-1449; eBioscience), and fluorescein isothiocyanate-(FITC)-labeled anti- CD51/CD61 (integrin alpha v beta3, 110519; eBioscience). For the PMP assay, platelet-poor plasma (50 μl) was incubated with 4 μl of FTIC-anti CD42b- (555472; BD Biosciences). All samples were incubated with antibodies at room temperature for 20 min and then diluted with 1 ml of phosphate-buffered saline buffer prior to analysis in a flow cytometer (Accuri C6; Accuri Cytometers). To ensure analysis of CD31+ EMP rather than platelet-derived CD31+ microparticles, CD42b- microparticles were analysed in platelet-poor plasma. Events calibrated by internal standard beads (0.8 μm; Sigma) were identified in forward-scatter and side-scatter modes gated on microparticles, and plotted on one- or two-color fluorescence histograms. The Accuri C6 flow cytometer can calculate the absolute number of microparticles in a sample. An isotype control antibody was used as a negative control in all experiments. EMP were defined as CD31+/CD42-, z. PMP were defined as CD31+ or CD42+. Values are expressed as counts/μl of peripheral blood. The laboratory personnel performing the assays were blinded to all clinical data.
Normally distributed data are expressed as the mean ± Standard Deviation (SD) and non-normally distributed data as the median and Inter-Quartile Range (IQR) or number. Variables were evaluated for normality using the Kol-mogorov-Smirnov test. The parametric Student’s t-test was used to compare quantitative variables between two groups of normally distributed data, and a non-parametric t-test was used for non-normally distributed data. The Chi-square test was used to compare quantitative and categorical variables. Spearman’s correlation analysis and multiple linear regression analysis were used to assess the relationship between different kinds of microparticles. Multiple linear regression analysis was used to determine the relationship between microparticles and clinical and laboratory variables. A P value of <0.05 was considered statistically significant. All statistical analyses were performed using SPSS 17.0 software.
Baseline data for the 33 patients and 53 healthy subjects are shown in Table 1. Clinical data included age, gender, Body Mass Index (BMI), Total Cholesterol (TC), High Density Lipoprotein (HDL) level, Low Density Lipoprotein (LDL) Level, Triglycerides (TG), and Diabetes Mellitus (DM). Any medications were also noted. Representative flow cytometry plots showing calibration with microparticle beads are shown in Figure 1. The data in Table 1 show that the control subjects were younger than CAD patients (p<0.001) and had a lower BMI (p<0.001). Healthy subjects had higher levels of HDL than the CAD group (P<0.001), whereas the CAD group had higher levels of LDL (p<0.05).
Figure 1: Representive flow cytometry plots of the number of circulating EMP. (a) The 0.8 µm calibrator beads, used to define the size of the microparticles, are represented on a side-scatter/forward-scatter dot plot. (b) Circulating microparticles are represented on a side-scatter/forward-scatter dot plot. S window was a gate of MP.
|Characteristics||Healthy controls||CAD patients||P value|
|Age (y)||34.26 ± 7.09 (53)||68.21 ± 12.786 (33)||<0.001|
|BMI (kg/m2)||22.45 ± 1.58 (53)||26.29 ± 3.66 (27)||<0.001|
|TC (mmol/l)||3.80 ± 0.39 (53)||4.05 ± 0.75 (25)||0.127|
|HDL (mmol/l)||1.37 ± 0.68 (53)||1.14 ± 0.28 (26)||<0.001|
|LDL (mmol/l)||1.94 ± 0.35 (53)||2.37 ± 0.77 (26)||0.011|
|LnTG (mmol/l)||0.39 ± 0.29 (53)||0.46 ± 0.64 (26)||0.599|
Values are expressed as the mean ± SD and (number)
CAD: Coronary Artery Disease; BMI: Body Mass Index; DM: Diabetes Mellitus; TC: Total Cholesterol; HDL: High Density Lipoprotein; LDL: Low Density Lipoprotein; TG: Triglycerides; CCBs: Calcium Channel Blockers. A P value of <0.05 was considered significant
Table 1: Demographic and clinical characteristics of the patients and healthy subjects.
Absolue numbers of EMP and PMP in CAD patients and healthy controls
The number of microparticles in samples from CAD patients and controls is shown in Table 2 and Figure 2. Figure 2 shows that the number of CD31+/CD42b- EMP and CD62E+ EMP was higher in CAD patients than in healthy controls (p<0.001 and p<0.05, respectively). As shown in Table 2, there was no significant difference in the number of CD144+ and CD51+ EMP, or the number of CD42b+ PMP, between CAD patients and controls.
|Characteristics||Healthy controls||CAD||P value|
|CD31+/CD42b- EMP||3.81 (1.48–9.84)||42.21 (8.80–103.63)||<0.001|
|CD144+ EMP||21.13 (9.33–36.71)||47.91 ± 45.74||0.086|
|CD62E+ EMP||2.84 ± 1.51||4.58 ± 3.49||0.011|
|CD51+ EMP||24.08 (8.22–55.79)||26.80 ± 25.10||0.342|
|CD42b+ PMP||38.83 (17.14–65.49)||20.26 (7.17–54.43)||0.120|
Values are expressed as the mean ± SD or as the median and inter-quartile range
CAD: Coronary Artery Disease; EMP: Endothelial Microparticle; PMP: Platelet
A P value <0.05 was considered significant
Table 2: Number of microparticles in patients and healthy subjects.
Correlation between different kinds of microparticle
Figure 3 shows the correlation between different kinds of microparticles, as determined by Spearman’s correlation and linear regression analysis. The data revealed a significant correlation between the number of CD31+/CD42b- EMP and the number of CD62E+ EMP (p=0.044; r=0.524).
Correlation between microparticles and clinical parameters
Multiple linear regression analysis was used to evaluate the relationship between independent variables (age, gender, BMI, TC, DM, HDL, LDL and TG) and dependent variables (ln(CD31+ EMP) and ln (CD62E EMP)). Because microparticle values were not normally distributed, we examined ln(microparticle) values. The results showed that neither CD62E+ EMP nor CD31+ EMP correlated with clinical parameters.
The major finding of this study is that endothelial activation and apoptosis, reflected by increased numbers of microparticles released from activated (CD62E+) and apoptotic (CD31+) endothelial cells, play an important role in CAD. These data provide insights into the mechanisms underlying endothelial dysfunction in CAD. There were no significant differences between the numbers of other types of EMP or PMP between patients and healthy subjects.
ED is a critical factor in the development and progression of CAD. EMP are membrane vesicles that are shed from endothelial cells in response to injury, activation, or apoptosis. EMP retain endothelial cell surface proteins and components of the cytosol, including enzymes, RNA, and micro (mi)RNA. The biological functions of EMP are related to inflammation, vascular tone, and coagulation [5,6]. The results of the present study show that the number of EMP is higher in CAD patients than in healthy controls, which is an indicator of endothelial apoptosis and activation in these patients. These results complement and extend the important findings of Nioks Werner et al. , who demonstrated that apoptotic EMP are involved in the pathogenesis of ED in CAD. A previous study showed that a CD62E+/CD31+ ratio ≤ 1.0 suggests that endothelial cell apoptosis plays the main role in the vessel damage associated with CAD . Here, we showed that the CD62E+/ CD31+ ratio in the CAD group was <1.0; significantly lower than that in the healthy group (p<0.001). Therefore, these results confirm that endothelial apoptosis plays the major role in the development of CAD.
Previous studies report that CAD patients have higher numbers of PMP [9,10] than healthy subjects; however, our data did not support this. The reasons for this may be 2-fold: (1) Leon Bernal-Mizrachi and his team  found that the number of PMP in patients with stable angina was no different from that in healthy subjects, but there was a difference between subjects who had experienced myocardial infarction and those with unstable angina. Thus, it appears that the number of PMP is related to the type of CAD (further experiments are needed to examine the role of PMP in different types of CAD); (2) Kiat et al.  reported that an increase in the number of PMP was not related to the extent of CAD. Therefore, the role of PMP in CAD requires further study; in the meantime, EMP may be more suitable as a biomarker for ED. Although the results in this paper are promising, two study limitations should be taken into account. One is that the sample sizes were small. The second is that the experimental approach was quite simplistic. Further experiments must be designed to examine the detailed mechanisms underlying the role of microparticles in CAD.
In conclusion, the results of the present study suggest that endothelial cell apoptosis plays the major role in the development of CAD. Therefore, it seems reasonable to suggest that EMPs have potential as biomarkers for monitoring ED. Future studies should aim to develop agents that inhibit EMP formation.
This study was supported by the National Natural Science Foundation of China (grant no. 11274046) and the Peking Union Medical College Innovation Funding (no. 3332013021).