Increased circulating leukocyte-derived microparticles in ischemic cerebrovascular disease

Thrombosis Research 154 (2017) 19–25

Contents lists available at ScienceDirect

Thrombosis Research journal homepage: www.elsevier.com/locate/thromres

Full Length Article

Increased circulating leukocyte-derived microparticles in ischemic cerebrovascular disease Zhangping He, Yanyan Tang, Chao Qin ⁎ Department of Neurology, First Affiliated Hospital, Guangxi Medical University, No. 22, Shuang Yong Road, Nanning 530021, Guangxi, China

a r t i c l e

i n f o

Article history: Received 27 August 2016 Received in revised form 8 March 2017 Accepted 30 March 2017 Available online 04 April 2017 Keywords: Ischemic cerebrovascular disease Vascular inflammatory Leukocyte-derived Microparticles

a b s t r a c t Objectives: Circulating leukocyte-derived microparticles act as proinflammatory mediators that reflect vascular inflammation. In this study, we examined the hypothesis that the quantity of leukocyte-derived microparticles is increased in patients with ischemic cerebrovascular diseases, and investigated utility of various phenotypes of leukocyte-derived microparticles as specific biomarkers of vascular inflammation injury. Additionally we focused on identifying leukocyte-derived microparticles that may be correlated with stroke severity in acute ischemic stroke patients. Methods: The plasma concentration of leukocyte-derived microparticles obtained by a series of centrifugations of 76 consecutive patients with ischemic cerebrovascular diseases and 70 age-, sex-, and race-matched healthy controls were determined by flow cytometry. Results: Significantly elevated numbers of leukocyte (CD45+), monocyte (CD14+), lymphocyte (CD4+), granulocyte (CD15+) derived microparticles were found in the plasma samples of patients ischemic cerebrovascular diseases, compared to healthy controls (p b 0.05). Furthermore, the plasma levels of CD14+ microparticles were significantly correlated with stroke severity (r = 0.355, p = 0.019), cerebral vascular stenosis severity (r = 0.255, p = 0.025) and stroke subtype (r = 0.242, p = 0.036). No association with stroke was observed for other leukocyte-derived phenotypes. Conclusions: These results demonstrate that circulating leukocyte-derived microparticles amounts are increased in patients with ischemic cerebrovascular diseases, compared with healthy controls. As proinflammatory mediators, leukocyte-derived microparticles may contribute to vascular inflammatory and the inflammatory process in acute ischemic stroke. Levels of CD14+ microparticles may be a promising biomarker of ischemic severity and outcome of stroke in the clinic. © 2017 Elsevier Ltd. All rights reserved.

1. Introduction According to World Health Organization (WHO) data, the global incidence of stroke varies widely [1]. Stroke is the second leading cause of death and the primary cause of disability in worldwide and 64.5% of stroke is ischemic cerebral stroke [2–4]. Atherosclerosis may be the main responsible for the occurrence of ischemic cerebral stroke. Vascular injury, endothelial cells dysfunction and inflammation are the three main initiation and development process of atherosclerosis [5,6]. We hypothesized that the interaction between modified lipoproteins, leukocyte and vascular cells plays an important role in the process of ischemic cerebral stroke. Processes, such as accumulation of harmful metabolites, proinflammatory mediators and cells death, aggravate atherosclerosis, eventually lead to ischemic cerebral stroke. Plasma microparticles (MPs) which range from 0.1 to 1 μm in size are submicron-sized membrane vesicles released by virtually all cell ⁎ Corresponding author. E-mail addresses: [email protected], [email protected] (C. Qin).

http://dx.doi.org/10.1016/j.thromres.2017.03.025 0049-3848/© 2017 Elsevier Ltd. All rights reserved.

types (in particular platelet, endothelial cells and leukocyte in the circulation) [7,8].When cells (such as leukocyte, erythrocytes, smooth muscle cells, endothelial cells and platelets) are activated and/or apoptosis in vivo, a large number of MPs are released [9–12]. MPs derived from different cellular types exert different biological effects. Platelet microparticles (PMPs) contribute to coagulation, inflammatory processes and thrombosis [13,14]. Endothelial microparticles (EMPs) generate endothelial dysfunction and angiogenesis [10,15]. The role of leukocytederived microparticles (LMPs) in disease progression is endothelial dysfunction and vascular inflammation, and is shown to be involved in the progressive formation and development of atherosclerotic plaque [16– 18]. LMPs are small particles originating from mature leukocyte which is immune cell and includes monocyte, lymphocyte and granulocyte upon cell activation and/or apoptosis [19]. LMPs are constantly present in the bloodstream and abnormal levels of LMPs have been found in various cardiovascular diseases, such as type 2 diabetes mellitus (T2D), thrombosis and coronary artery disease [20,21]. LMPs express surface CD45 antigen. Monocyte, lymphocyte and granulocyte express surface CD14, CD4, CD15 antigens respectively. The presence of distinct antigen

20

Z. He et al. / Thrombosis Research 154 (2017) 19–25

molecules provides a useful means to distinguish different phenotypes of LMPs. In the present study, we quantified various circulating LMPs phenotypes in patients with ischemic cerebrovascular diseases (ICVD) in comparison to control subjects. Our main objective was to establish whether the circulating LMPs quantity is increased in acute ischemic stroke patients and the potential utility of specific LMPs as new proinflammatory mediators of vascular inflammation, which open interesting perspectives in clinical settings by specific LMPs detection and enumeration using flow cytometry in atherosclerosis and stroke [22]. Whether are LMPs also shown to be a relationship between their levels and their metrocyte levels? Additionally we focused on identifying the LMPs phenotypes that may be effectively applied as promising biomarkers of stroke severity, cerebral vascular stenosis (CVS) severity and outcome in acute ischemic stroke patients. 2. Materials and methods Ethical approval for this study was obtained from the Institutional Review Board of the First Affiliated Hospital of Guangxi Medical University and informed consent complying with the Declaration of Helsinki was signed by all participants [23–25]. 2.1. Subjects Within 7 days of clinical symptom onset, seventy-six ischemic stroke patients (age range 57-81 years) who comprised inpatients at the Neurology Department in the First Affiliated Hospital of Guangxi Medical University (Guangxi, Nanning, China) between June 2015 and June 2016 were eligible for enrollment. Physical and neurological assessments were conducted for all patients who underwent perfusion weighted imaging examination via either computed tomography (CT) or magnetic resonance imaging (MRI). Additionally, all patients also underwent computed tomography angiography (CTA) checking to find cerebral vascular stenosis severity. Ischemic stroke severity was measured using National Institutes of Health Stroke Scale (NIHSS) [26], whereby scores b5 were defined as “mild ICVD” and ≥5 as “moderate-severe ICVD” and cerebral vascular stenosis (CVS) severity was measured using North American Symptomatic Carotid Endarterectomy Trial (NASCET) [27] clinical criteria, whereby a b 70% reduction in diameter was defined as “mild/moderate-grade CVS” and a ≥70% reduction in diameter was defined as “high-grade CVS”. Acute ischemia stroke was classified into the following two subtypes according to the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) [28] system: large-artery atherosclerosis (L), small-vessel occlusion (S), cardioembolism (CE), and stroke of undetermined etiology (U), and according to the Oxfordshire Community Stroke Project (OCSP) [29]: total anterior circulation infarct (TACI), partial anterior circulation infarct (PACI), posterior circulation infarct (POCI), lacunar infarct (LACI) and uncertain. During the inclusion period, a group of seventy age-, sex-, and race-matched healthy individuals (age range 59–84 years) who were volunteers admitted to the Medical Center in the First Affiliated Hospital of Guangxi Medical University (Guangxi, Nanning, China) with no history of ischemic stroke and cerebral vascular stenosis were recruited for the study as controls. The all subjects had no renal or hepatic disease, inflammatory disease, hematological disorders, cardiovascular disease, chronic diseases, autoimmune or malignant disease. Similarly, none of the subjects were taking anticoagulants or anti-platelet drugs. 2.2. Isolation and detection of circulating plasma LMPs 6 mL of venous blood from each of the 146 participants was collected into 0.129 mol/L tri-sodium citrate tubes after an overnight fasting. Platelet-poor plasma (PPP) was prepared within 1 h of blood collection by two serial centrifugations. Briefly, LMPs were obtained by centrifuged at 1700 × g for 10 min at 4 °C to remove blood cells, then

supernatant followed by centrifugation at 3000 × g for 30 min at 4 °C to obtain PPP, and stored at − 80 °C until measurement of LMPs. In our preliminary experiments, we use enzyme linked immunosorbent assay (ELISA) to validate and support existence of MPs by combining Annexin V with phosphatidylserine (PS) on MPs surface, and LMPs counts remained stable by centrifuged at different temperature (4 °C,10 °C and room temperature). Meanwhile, in our preliminary experiments, no significant difference in the MPs levels was found when analyzed with fresh plasma or plasma underwent a freeze-thaw cycle. For flow cytometry analysis, frozen PPP was thawed in a 37 °C water bath for 5 min. For the LMPs labeling, 100 μl freshly thawed PPP was incubated for 15 min in the dark at 4 °C with the following fluorescent conjugated monoclonal antibodies: PECy5.5-conjugated anti-human CD45 (leukocyte-derived microparticles) (5 μl, eBioscience, San Diego, USA), PE - conjugated anti-human CD14 (monocyte-derived microparticles) (5 μl, eBioscience, San Diego, USA), fluorescein isothiocyanate (FITC)-conjugated-anti-human CD4 (lymphocyte-derived microparticles) (5 μl, eBioscience, San Diego, USA) and fluorescein isothiocyanate (FITC)-conjugated-anti-human CD15 (granulocyte-derived microparticles) (5 μl, eBioscience, San Diego, USA); isotype-matched (IgG) nonspecific antibodies were added to another sample tube as a negative control; then diluted with 1 mL of phosphate buffer solution (PBS). All samples were shaken gently and analyzed on flow cytometry assay (Accuri-C5, BD Biosciences, USA) at the low rate setting. LMPs were measured using both forward scatter (FSC) and side scatter (SSC) and LMPs population was restricted by size (FSC area 104–105) and complexity (SSC area 104–105). The cellular origin of LMPs was identified via simultaneous detection of antigens on the surface. Absolute counting beads 2 μm in diameter (Spherotech, Inc., USA) were used for size calibration (Fig. 1). LMPs were defined as particles smaller than 2 μm. Amount of LMPs were quantified and recorded as counts per μl PPP (counts/μl). To meet with normal distribution, LMPs values were analyzed after log transformation. So the final values of LMPs were expressed as log-transformed counts per μl (log LMPs/μl). All blood samples were analyzed by skilled technicians blinded to clinical data. 2.3. Statistical analysis Statistical analysis was performed using SPSS 18.0 software (Inc., Chicago, IL). LMPs values after log transformation (on a base 10 scale) were analyzed to meet with normal distribution. Continuous variables for measurement date were expressed as mean values ± standard deviation (SD) and handled by two-tailed, unpaired Student-t-test or oneway ANOVA. Continuous variables also were analyzed by KolmogorovSmirnov teat. Categorical variables of baseline data were expressed as percentage and Chi-Square test for categorical variables of baseline data between healthy controls and patients was conducted. Spearman's r test for bivariate correlations was conducted. Random variables were measured with linear regression model. A p-value b 0.05 was considered statistically significant. 3. Results 3.1. Biological parameters of the study subjects In this study, a total of 146 subjects, including 76 patients with ICVD and 70 healthy controls were recruited. The average age was 62.61 ± 11.26 years for the patient group and 63.34 ± 9.59 years for the control group. Two groups were matched in terms of age, sex, prevalence of risk factors (hypertension, diabetes, dyslipidemia, smoking), white blood cell (monocyte, lymphocyte, granulocyte), and lipid profiles. The levels of circulating CD45 + white blood cells (white blood cells and leukocytes are the same), CD14+ monocytes, CD4+ lymphocytes, CD15 + granulocytes were within the normal range and different in both stroke and control groups, but not to a statistically significant extent (p =

Z. He et al. / Thrombosis Research 154 (2017) 19–25

21

Fig. 1. Scatter plot of LMPs cytofluorometry analysis: A: all microparticles in PPP; P1: gating according to the standard beads; B: Isotype control; C: microparticles in control group; P2: CD45+ LMPs in control group; D: microparticles in ischemic cerebrovascular disease patients group; P3: CD45+ LMPs in ischemic cerebrovascular disease patients group.

0.061, 0.488, 0.132, 0.746 respectively, Student's t-test). Notably, compared with the control group, the patient group had greater in CRP and fibrinogen levels (p = 0.005, p = 0.039, respectively, Student's ttest). Specific biological parameters and clinical date of the study subjects are showed in Table 1.

phenotypes (CD45+, p = 0.001; CD14+, p = 0.017) in mild ICVD patients and (CD45 +, p = 0.002; CD14 +, p = 0.004; CD15 +, p = 0.042) in mild-grade CVS patients were significantly greater, compared to the control group. All results are summarized in Table 2 and in Figure 1.

3.2. LMPs levels in patients with ischemic cerebrovascular disease

3.3. Correlation between LMPs phenotypes and clinical parameters

To meet with normal distribution, LMPs levels were calculated via log-transformation (on a base 10 scale). Using Student's t-test, CD45+ LMPs (p = 0.027), CD14 + monocyte-derived microparticles (p = 0.013), CD4 + lymphocyte-derived microparticles (p = 0.038), CD15 + granulocyte-derived microparticles (p = 0.021) levels in patient group were significantly increased than those in the control group. Moreover, CD45+ (p b 0.000), CD14+ (p b 0.000), CD4+ (p = 0.002), CD15 + (p = 0.009) LMPs in moderate-severe ICVD patients and CD45 + (p b 0.000), CD14 + (p b 0.000), CD4 + (p = 0.015), CD15+ (p = 0.007) LMPs in high-grade CVS patients were significantly higher compared to the control group. The CD4 + and CD15 + LMPs levels in mild ICVD patients were similar, relative to the control group (p = 0.097, p = 0.093, respectively, Student's t-test) and the CD4 + LMPs level in mild-grade CVS patients were also similar, compared to the control group (p = 0.082, Student's t-test). The other LMPs

All patients with ICVD were divided into subgroups according to age, sex, NIHSS score, NASCET classification and stroke subtypes (TOAST and OCSP classification systems) to investigate LMPs phenotypes distribution. No significant differences in LMPs levels were found in these subgroups among patients with ICVD, except NIHSS score and NASCET classification. In CD14 + monocyte-derived microparticles levels, patients with NIHSS scores ≥5 were significant differences, compared to NIHSS scores b 5 (p = 0.024), and patients with NASCET classification ≥70% reduction in diameter showed significant differences, compared with b70% reduction in diameter (p = 0.017). Detail on age, sex, NIHSS score, NASCET classification and stroke subtypes are shown in Table 3. Correlations between different LMPs phenotypes were evaluated. The relationship between CD45+ and CD14+ LMPs was not significant, indicating different mechanisms in these two LMPs types since they origin from different kinds of cells with various biological

22

Z. He et al. / Thrombosis Research 154 (2017) 19–25

Table 1 Baseline characteristics of the study subjects.

Table 3 Correlations between LMPs and clinical parameter.

Control group (n = 70)

ICVD group (n = 76)

p-value

All patients (n = 76)

CD45+ mean ± SD

CD14+ mean ± SD

CD4+ mean ± SD

15+ mean ± SD

Mean age ± SD, (years) Male sex, n (%) Hypertension, n (%) Diabetes, n (%) Hyperlipidemia, n (%) Smoking, n (%)

63.34 ± 9 44 (62.86) 42 (60.00) 12 (17.14) 33 (47.14) 26 (37.14)

62.61 ± 11.26 58 (76.32) 44 (57.89) 19 (25.00) 30 (39.47) 30 (39.47)

0.672 0.077 0.796 0.246 0.350 0.865

p = 0.064 1.70 ± 0.88

p = 0.102 3.29 ± 0.86

p = 0.299 1.22 ± 0.75

p = 0.996 2.30 ± 0.98

1.66 ± 1.02

3.28 ± 0.96

1.17 ± 0.80

2.22 ± 1.02

Clinical date (CD45+) WBC (/L × 109) (CD14+) MONO (/L × 109) (CD4+) LYM (/L × 109) (CD15+)GRA (/L × 109) Glucose (mmol/L) CRP (mg/L) Fibrinogen (g/L)

6.95 ± 2.14 0.59 ± 0.23 2.13 ± 0.86 5.12 ± 3.36 5.02 ± 1.70 0.59 ± 1.03 3.45 ± 0.73

7.74 ± 2.86 0.62 ± 0.25 1.94 ± 0.66 4.95 ± 2.76 5.47 ± 1.88 1.26 ± 1.31 4.13 ± 1.05

0.061 0.488 0.132 0.746 0.129 0.005⁎ 0.039⁎

p = 0.149 1.58 ± 0.90 2.04 ± 0.93 p = 0.392 1.61 ± 0.90 1.76 ± 0.95 p = 0.109

p = 0.906 3.33 ± 0.93 3.12 ± 0.72 p = 0.024⁎ 3.20 ± 0.91 3.38 ± 0.87 p = 0.017⁎

p = 0.657 1.23 ± 0.79 1.11 ± 0.69 p = 0.892 1.14 ± 0.74 1.26 ± 0.79 p = 0.176

p = 0.423 2.35 ± 0.98 2.05 ± 0.99 p = 0.061 2.08 ± 0.99 2.45 ± 0.96 p = 0.051

1.54 ± 0.84 1.84 ± 0.99

3.06 ± 0.94 3.52 ± 0.78

1.07 ± 0.81 1.34 ± 0.70

2.11 ± 0.94 2.45 ± 1.01

Lipid profiles (mmol/L) Total cholesterol Triglycerides HDL LDL

5.27 ± 1.06 1.50 ± 0.77 1.52 ± 0.36 3.05 ± 0.89

5.00 ± 1.58 1.53 ± 1.17 1.45 ± 0.40 2.74 ± 1.17

0.216 0.881 0.283 0.082

Age, (years) Age ≥60 (n = 48) Age b60 (n = 28) Sex Male (n = 58) Female(n = 18) NIHSS score b5 (n = 35) ≥5 (n = 41) NASCET classification b70% (n = 39) ≥70% (n = 37) Stroke subtype TOAST classification L (n = 40) S (n = 21) CE (n = 12) U (n = 3) OCSP classification TACI (n = 10) PACI (n = 31) POCI (n = 19) LACI (n = 16) Uncertain (n = 0)

p = 0.612

p = 0.058

p = 0.438

p = 0.864

2.21 ± 0.65 1.95 ± 0.58 1.65 ± 0.72 1.69 ± 0.41 p = 0.308

3.57 ± 0.93 2.54 ± 0.67 2.97 ± 0.81 2.71 ± 0.54 p = 0.147

1.49 ± 0.67 1.02 ± 0.89 1.13 ± 0.49 1.26 ± 0.61 p = 0.547

2.57 ± 0.77 2.41 ± 0.68 1.99 ± 0.53 2.01 ± 0.41 p = 0.264

1.62 ± 0.55 1.92 ± 0.61 2.03 ± 0.67 1.76 ± 0.65 0

2.28 ± 0.99 3.39 ± 0.58 2.69 ± 0.71 3.58 ± 0.96 0

1.15 ± 0.21 1.61 ± 0.76 1.24 ± 0.51 1.18 ± 0.33 0

2.34 ± 0.46 1.98 ± 0.79 2.54 ± 0.65 2.13 ± 1.01 0

Note: date are expressed by mean ± SD or percentage, ICVD = ischemic cerebrovascular disease; WBC = white blood cell or leukocyte, MONO = monocyte; LYM = lymphocytes; GRA = granulocyte; CRP = C-reactive protein; HDL = high-density lipoprotein; LDL = low-density lipoprotein. ⁎ p b 0.05 compared to control group.

functions. Additionally, correlations between LMPs phenotypes and demographic data, risk factors and laboratory parameters in patients with ICVD were also analyzed. No significant correlations were evident between these LMPs phenotypes examined and patient with ICVD clinical data, except CD14+ monocyte -derived microparticles. Using Pearson's r test, levels of CD14+ monocyte -derived microparticles were significantly correlated with stroke severity (r = 0.355, p = 0.019), cerebral vascular stenosis severity (r = 0.255, p = 0.025) and stroke subtypes (r = 0.242, p = 0.036), based on TOAST classification. Details on correlations between different LMPs phenotypes and demographic data, risk factors and laboratory parameters are shown in Table 4. The patient clinical parameters had no effects on LMPs levels in the circulation (multivariate linear regression model), these results are shown in Table 5. 4. Discussion Vascular inflammation is a crucial element in the development and progression of atherosclerosis and ICVD, more and more evidence illustrates inflammation can lead to disease progression and worsens disease severity and outcome [30]. Various pathophysiological processes such as apoptosis, proinflammatory mediators, oxidative stress, oxidized low density lipoprotein (oxLDL) and so on can cause vascular inflammation, thereby causing changes in vascular endothelial cell dysfunction and vascular permeability. LMPs harbor antigens of their

Note: all results are present as mean ± SD after log-transformation; L = large-artery atherosclerosis; S = small-vessel occlusion; CE = cardioembolism; U = undetermined etiology; TACI = total anterior circulation infarcts; PACI = partial anterior circulation infarcts; POCI = posterior circulation infarcts; LACI = lacunar infarct. ⁎ p b 0.05.

parental cells which not only allow us to distinguish LMPs from other blood substances and different LMPs phenotypes, but also make LMPs a potentially valuable biological marker of vascular inflammation and allow their detection by flow cytometry. In this way, CD45, CD14, CD4 and CD15 are markers of microparticles released from leukocyte, monocyte, lymphocyte and granulocyte, respectively. The coexpression of leukocyte-derived microparticles is CD45. Therefore, we chose CD45+ MPs as a marker to evaluate the circulation LMPs level, which expressed by leukocytes. Studies on the coexpression of CD45 and other leukocyte antigens on microparticles revealed that CD45 was not expressed on 100% of leukocyte-derived microparticles [31]. The CD14 +, CD4 + and CD15 + MPs have been linked inflammation, vascular injury and atherosclerosis. Because volunteers exposed to endotoxin exhibit an early increase in circulating tissue factor (TF +, a potent activator of the coagulation cascade) MPs, which are mainly CD14+ monocyte-derived microparticles [32,33], we use CD14+ MPs to mark monocyte-derived microparticles related with disseminated intravascular

Table 2 The levels of LMPs in ICVD group and control group. LMPs phenotype (count/ul)

Control group (n = 70)

All ICVD patients (n = 76)

Mild ICVD patients (n = 35)

Moderate-severe ICVD patients (n = 41)

Mild/moderate-grade CVS patients (n = 39)

High-grade CVS patients (n = 37)

CD45+

1.24 ± 0.78 2.73 ± 0.74

1.61 ± 0.90 p = 0.001⁎ 3.20 ± 0.91 p = 0.017⁎

1.76 ± 0.95 p b 0.000⁎

CD14+

1.69 ± 0.92 p = 0.027⁎ 3.28 ± 0.89 p = 0.013⁎

3.38 ± 0.87 p b 0.000⁎

1.54 ± 0.84 p = 0.002⁎ 3.06 ± 0.94 p = 0.004⁎

1.84 ± 0.99 p b 0.000⁎ 3.52 ± 0.78 p b 0.000⁎

CD4+

0.91 ± 0.62

CD15+

1.87 ± 0.56

1.20 ± 0.76 p = 0.038⁎ 2.28 ± 0.99 p = 0.021⁎

1.14 ± 0.74 p = 0.097 2.08 ± 0.99 p = 0.093

1.26 ± 0.79 p = 0.002⁎ 2.45 ± 0.96 p = 0.009⁎

1.07 ± 0.81 p = 0.082 2.11 ± 0.94 p = 0.042⁎

1.34 ± 0.70 p = 0.015⁎ 2.45 ± 1.01 p = 0.007⁎

Note: all results are present as mean ± SD after log-transformation; ICVD = ischemic cerebrovascular disease, CVS = cerebral vascular stenosis. ⁎ p b 0.05 compared to control group.

Z. He et al. / Thrombosis Research 154 (2017) 19–25

23

Table 4 Correlations between LMPs and baseline data. Demographic

CD45+

Age Sex Hypertension Diabetes Hyperlipidemia Smoking WBC (/L × 109) MONO (/L × 109) LYM (/L × 109) GRA (/L × 109) Glucose (mmol/L) Stroke severity NASCET classification TOAST classification OCSP classification

CD14+

CD4+

CD15+

r

p

r

p

r

p

r

p

0.078 −0.206 −0.009 0.250 0.139 0.314 −0.087 −0.123 −0.182 −0.040 0.168 0.112 0.145 −0.158 0.118

0.501 0.074 0.942 0.059 0.230 0.061 0.454 0.288 0.116 0.729 0.146 0.336 0.211 0.187 0.251

0.041 0.111 −0.06 0.137 −0.039 −0.412 0.014 0.064 −0.220 0.038 0.126 0.356 0.255 0.242 0.215

0.723 0.341 0.609 0.237 0.740 0.093 0.908 0.584 0.056 0.746 0.278 0.019⁎ 0.025⁎ 0.036⁎

−0.025 0.059 −0.087 0.088 −0.037 0.028 0.020 0.003 −0.106 0.016 0.050 −0.063 0.220 0.072 −0.285

0.833 0.615 0.456 0.450 0.752 0.841 0.862 0.981 0.362 0.888 0.670 0.588 0.056 0.314 0.201

−0.022 0.068 −0.087 0.029 −0.061 0.053 0.041 −0.055 −0.163 0.053 0.1560.178 −0.181 −0.176 0.650.323 0.295

0.847 0.557 0.452 0.803 0.602 0.473 0.723 0.637 0.159 0.650

0.069

0.117 0.127 0.078

⁎ p b 0.05.

coagulation. In addition, CD4 staining was observed in vessels from in vivo-treated mice and CD4 labeling was related to an infiltration of in vivo monocytes-macrophages into the media layer of the vessel wall, CD4+ MPs interacting with smooth muscle cells through carrying Fas ligand (FasL) on their surface evoked nuclear factor kappa B activation and up-regulated nitric oxide synthase and cyclooxygenase-2 expression [34], so CD4 + MPs were used to represent lymphocyte-derived microparticles. Present in granulocyte, CD15+ MPs mediate their binding to P-selectin on activated platelets and captured by activated platelets within thrombi by a P-selectin/P-selectin glycoprotein 1 (PSGL-1)dependent mechanism [20,31,35]. Thus we have chosen CD15+ MPs as a marker of granulocyte-derived microparticles, too. The relationships among CD45+ MPs, CD14+ MPs, CD4+ MPs, CD15+ MPs and stroke have not been extensively studied; thus, the aim of this study was to investigate these associations. In present study, we explored the profiles of various LMPs phenotypes in patients with ICVA, compared with control subjects. Several published studies to date have focused on vascular disease. Leroyer et al. [19] reached a similar conclusion when detecting LMPs levels in patients undergoing carotid endarterectomy, most plaque microparticles originated from three types of LMPs: CD14+ monocyte-derived microparticles (29 ± 5%), CD4+ lymphocyte-derived microparticles (15 ± 3%), CD66b+ granulocyte-derived microparticles (8 ± 1%), and plaques from asymptomatic and symptomatic patients showed no differences in microparticle origins. In an earlier investigation of LMPs profiles in asymptomatic patients with high-grade carotid stenosis by Gabrielle et al. [36], significantly higher levels of three LMPs phenotypes

Table 5 Correlations between LMPs levels and clinical parameters. Risk factors

CD45+ p

CD14+ p

CD4+ p

CD15+ p

Age Sex Hypertension Diabetes Hyperlipidemia Smoking WBC MONO LYM GRA Stroke severity NASCET classification TOAST classification OCSP classification

0.893 0.251 0.574 0.442 0.131 0.663 0.067 0.579 0.227 0.315 0.221 0.061 0.124 0.597

0.651 0.903 0.273 0.227 0.793 0.373 0.862 0.059 0.652 0.435 0.069 0.075 0.237 0.211

0.906 0.235 0.873 0.531 0.353 0.312 0.251 0.792 0.263 0.547 0.197 0.996 0.965 0.600

0.269 0.654 0.210 0.115 0.991 0.517 0.318 0.553 0.475 0.107 0.343 0.943 0.675 0.608

(CD15 +, CD11b +, CD66b+) in patients with unstable plaque, compared to patients with stable plaque, in particular, the level of CD11b + CD66b + MPs and the neurologic symptoms independently predicted plaque instability. Enjeti and colleagues [37] reported that circulating CD45 + LMPs were elevated in subjects who were heterozygote for factor V leiden and might be important contributors to risk of thrombosis. Another study by Zhou et al. [38] explored that CD45 + LMPs levels were significantly decreased immediately in patients after percutaneous transluminal coronary intervention (PCI) and log-normalized high sensitivity-c-reative-protein was also significantly correlated with CD45 + LMPs. Omoto and workers [39] explored CD14 + MPs levels in T2D patients. Elevated CD14+ MPs levels have been detected in T2D patients compared to normal subjects. Within the patient population, diabetic patients with complications (such as nephropathy, neuropathy, retinopathy and so on) had higher concentrations of CD14+ MPs compared with diabetics patients without complications. Additionally CD14+ MPs levels were especially high in the T2D patients with nephropathy, which could be a useful indicator of nephropathy progression in the diabetic. In the current study, levels of four LMPs phenotypes in patients with ICVD were significantly higher compared to those in control individuals and were consistent with previous finding. The specific pathophysiological mechanism underlying the elevation of circulating LMPs in patients with ICVD remains to be established. The problem of whether LMPs induce or are generated as a response to arteriosclerosis and ICVD requires confirmation. In our study, the roles for thrombosis and inflammation are likely because significant elevation of C-reactive protein and fibrinogen were noted in patients with ICVD. CD45 and CD14 are constitutive markers of leukocytes and monocytes/macrophages, respectively [37,39]. The levels of CD45 + and CD14+ MPs provide an index of thrombosis and vascular inflammatory in various diseases [32,33]. Thus, increased levels of CD14+ MPs may reflect vascular inflammatory in ICVD. As a specific phenotype of LMPs, CD14+ MPs are significantly associated with indices of neurological damage in ICVD (NIHSS scores) which supports CD14+ MPs as an independent biomarker of stroke severity to reveal the extent of ischemia. Additionally, CD14+ MPs are also significantly associated with CVS based on NASCET classification. The observation that LMPs levels are correlated with the degree of CVS is consistent with previous findings [19,36]. Our results showed a mild correlation between CD14 + MPs levels and stroke subtype (TOAST classification), indicating a relationship between CD14+ MPs and reason of ischemia lesions. No significant correlation was evident between the remaining phenotypes of LMPs and stroke severity index, CVS severity and stroke subtypes, although significantly greater levels of those LMPs phenotypes were observed in patients with ICVD. Our current results provide evidence of a strong correlation between vascular inflammation resulted in LMPs and

24

Z. He et al. / Thrombosis Research 154 (2017) 19–25

ischemia severity in patients with ICVD. These findings also provide also provide an important insight into the potential predictive value of CD14+ MPs in stroke severity and CVS severity. The pro-inflammatory effect of LMPs is mainly seen through increased production of tumor necrosis factora, IL-6, IF-8, activated protein C and IF-1ß [40,41], especially, monocyte/macrophage-derived microparticles induced translocation of NF-k B into the nucleus, leading to the increased production of IF-8 and monocyte chemoattractant protein 1 [42,43]. Monocyte/macrophage-derived microparticles additionally induced brain endothelial cells to undergo vesiculation and produce EMPs [17]. Their date support LMPs as potential roles of biomarkers in mechanisms of inflammation and IVCD. However the process of inflammation also can release numerous small molecular biomarkers (such as microparticles, cytokines and chemokines). The issue of whether LMPs lead to inflammation or inflammation generates a lot of LMPs in ICVD. Obviously, this issue will require further study. The present study has some potential limitations. We still have very limited information about the type of LMPs to be assessed and the bioactive molecules to be employed as a cardiovascular risk marker. For detecting MPs, although standard flow cytometry is an established method. Due to detection restrictions and possible swarm detection, particles smaller than 0.5 μm in size cannot be detected accurately using flow cytometry which may lead to the underestimation of LMPs. As promising new techniques, dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) can determine the absolute size distribution, but require further research. In the same way, it is absent for patient with ICVD follow-up regarding neurologic events. The issue of whether plasma levels of LMPs can predict ischemic and CVS severity is needed to establish using large-scale prospective studies. In summary, this present works provides evidence that CD45 +, CD14 +, CD4 +, CD15 + MPs are present in the human circulation, with elevated levels in patients with ICVD. Especially, increased circulating CD14+ MPs levels may be useful in identifying ischemic severity among the patients with ICVD. CD14+ MPs are additionally associated with CVS severity and ischemic categories. Therefore, high level of CD14+ MPs may be used as biomarkers of vascular inflammation injury and a potential valuable predictor of cardiovascular outcome in acute ischemic stroke patients. Although CD14+ MPs may be a marker of cardiovascular risk, we are far from its application in the clinical practice. Future research may focus on the functional importance of LMPs phenotypes in patients with ICVD. Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article. Acknowledgements This research was supported by the National Natural Science Foundation of China (No. 81360191) and Youth Science Foundation of Guangxi Medical University (GXMUYSF2014029). References [1] V.L. Feigin, C.M. Lawes, D.A. Bennett, C.S. Anderson, Stroke epidemiology: a review of population-based studies of incidence, prevalence, and case-fatality in the late 20th century, Lancet Neurol. 2 (1) (2003) 43–53. [2] M. Liu, B. Wu, W.Z. Wang, L.M. Lee, S.H. Zhang, L.Z. Kong, Stroke in China: epidemiology, prevention, and management strategies, Lancet Neurol. 6 (5) (2007) 456–464. [3] B. Jiang, W.Z. Wang, H. Chen, Z. Hong, Q.D. Yang, S.P. Wu, X.L. Du, Q.J. Bao, Incidence and trends of stroke and its subtypes in China: results from three large cities, Stroke 37 (1) (2006) 63–68. [4] V. Sisirak, B. Sally, V. D'Agati, W. Martinez-Ortiz, Z.B. Ozcakar, J. David, A. Rashidfarrokhi, A. Yeste, C. Panea, A.S. Chida, M. Bogunovic, I.I. Ivanov, F.J. Quintana, I. Sanz, K.B. Elkon, M. Tekin, F. Yalcinkaya, T.J. Cardozo, R.M. Clancy, J.P. Buyon, B. Reizis, Digestion of chromatin in apoptotic cell microparticles prevents autoimmunity, Cell 166 (1) (2016) 88–101.

[5] Y. Gursoy-Ozdemir, A. Can, T. Dalkara, Reperfusion-induced oxidative/nitrative injury to neurovascular unit after focal cerebral ischemia, Stroke 35 (6) (2004) 1449–1453. [6] K.H. Jung, K. Chu, S.T. Lee, H.K. Park, J.J. Bahn, D.H. Kim, J.H. Kim, M. Kim, S. Kun Lee, J.K. Roh, Circulating endothelial microparticles as a marker of cerebrovascular disease, Ann. Neurol. 66 (2) (2009) 191–199. [7] M.L. Coleman, E.A. Sahai, M. Yeo, M. Bosch, A. Dewar, M.F. Olson, Membrane blebbing during apoptosis results from caspase-mediated activation of ROCK I, Nat. Cell Biol. 3 (4) (2001) 339–345. [8] M. Diamant, M.E. Tushuizen, A. Sturk, R. Nieuwland, Cellular microparticles: new players in the field of vascular disease? Eur. J. Clin. Investig. 34 (6) (2004) 392–401. [9] Z.H. Wu, C.L. Ji, H. Li, G.X. Qiu, C.J. Gao, X.S. Weng, Membrane microparticles and diseases, Eur. Rev. Med. Pharmacol. Sci. 17 (18) (2013) 2420–2427. [10] D. Burger, M. Turner, M.N. Munkonda, R.M. Touyz, Endothelial microparticle-derived reactive oxygen species: role in endothelial signaling and vascular function, Oxidative Med. Cell. Longev. 2016 (2016) 5047954. [11] A.E. Berezin, A.A. Kremzer, T.A. Berezina, Y.V. Martovitskaya, The pattern of circulating microparticles in patients with diabetes mellitus with asymptomatic atherosclerosis, Acta Clin. Belg. 71 (1) (2016) 38–45. [12] G. Levin, E. Sukhareva, A. Lavrentieva, Impact of microparticles derived from erythrocytes on fibrinolysis, J. Thromb. Thrombolysis 41 (3) (2016) 452–458. [13] M.S. Williams, H.L. Rogers, N.Y. Wang, R.C. Ziegelstein, Do platelet-derived microparticles play a role in depression, inflammation, and acute coronary syndrome? Psychosomatics 55 (3) (2014) 252–260. [14] S. Mezouar, D. Mege, R. Darbousset, D. Farge, P. Debourdeau, F. Dignat-George, L. Panicot-Dubois, C. Dubois, Involvement of platelet-derived microparticles in tumor progression and thrombosis, Semin. Oncol. 41 (3) (2014) 346–358. [15] S. Tual-Chalot, F. Gagnadoux, W. Trzepizur, P. Priou, R. Andriantsitohaina, M.C. Martinez, Circulating microparticles from obstructive sleep apnea syndrome patients induce endothelin-mediated angiogenesis, Biochim. Biophys. Acta 1842 (2) (2014) 202–207. [16] M. Hjuler Nielsen, H. Irvine, S. Vedel, B. Raungaard, H. Beck-Nielsen, A. Handberg, Elevated atherosclerosis-related gene expression, monocyte activation and microparticle-release are related to increased lipoprotein-associated oxidative stress in familial hypercholesterolemia, PLoS One 10 (4) (2015) e0121516. [17] B. Wen, V. Combes, A. Bonhoure, B.B. Weksler, P.O. Couraud, G.E. Grau, Endotoxininduced monocytic microparticles have contrasting effects on endothelial inflammatory responses, PLoS One 9 (3) (2014) e91597. [18] F.F. Hoyer, M.K. Giesen, C. Nunes Franca, D. Lutjohann, G. Nickenig, N. Werner, Monocytic microparticles promote atherogenesis by modulating inflammatory cells in mice, J. Cell. Mol. Med. 16 (11) (2012) 2777–2788. [19] A.S. Leroyer, H. Isobe, G. Leseche, Y. Castier, M. Wassef, Z. Mallat, B.R. Binder, A. Tedgui, C.M. Boulanger, Cellular origins and thrombogenic activity of microparticles isolated from human atherosclerotic plaques, J. Am. Coll. Cardiol. 49 (7) (2007) 772–777. [20] M.G. Huisse, E. Lanoy, D. Tcheche, L.J. Feldman, A. Bezeaud, E. Angles-Cano, M. MaryKrause, D. de Prost, M.C. Guillin, P.G. Steg, Prothrombotic markers and early spontaneous recanalization in ST-segment elevation myocardial infarction, Thromb. Haemost. 98 (2) (2007) 420–426. [21] U. Rauch, D. Bonderman, B. Bohrmann, J.J. Badimon, J. Himber, M.A. Riederer, Y. Nemerson, Transfer of tissue factor from leukocytes to platelets is mediated by CD15 and tissue factor, Blood 96 (1) (2000) 170–175. [22] J.G. Wang, E. Aikawa, M. Aikawa, Leukocyte-derived microparticles as proinflammatory mediators in atherosclerosis, J. Am. Coll. Cardiol. 62 (16) (2013) 1442–1445. [23] WMA, Declaration of Helsinki serves as guide to physicians, Calif. Med. 105 (2) (1966) 149–150. [24] L.J. Bruce-Chwatt, Declaration of Helsinki. Recommendations guiding doctors in clinical research, WHO Chron. 19 (1965) 31–32. [25] P.P. Rickham, Human experimentation. Code of ethics of the world medical association. Declaration of Helsinki, Br. Med. J. 2 (5402) (1964) 177. [26] L.B. Goldstein, C. Bertels, J.N. Davis, Interrater reliability of the NIH stroke scale, Arch. Neurol. 46 (6) (1989) 660–662. [27] Beneficial effect of carotid endarterectomy in symptomatic patients with high-grade carotid stenosis, N. Engl. J. Med. 325 (7) (1991) 445–453. [28] H.P. Adams Jr., B.H. Bendixen, L.J. Kappelle, J. Biller, B.B. Love, D.L. Gordon, E.E. Marsh 3rd, Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment, Stroke 24 (1) (1993) 35–41. [29] J. Ilzecka, Z. Stelmasiak, Practical significance of ischemic stroke OCSP (Oxfordshire Community Stroke Project) classification, Neurol. Neurochir. Pol. 34 (1) (2000) 11–22. [30] K.W. Muir, P. Tyrrell, N. Sattar, E. Warburton, Inflammation and ischaemic stroke, Curr. Opin. Neurol. 20 (3) (2007) 334–342. [31] M.G. Macey, N. Enniks, S. Bevan, Flow cytometric analysis of microparticle phenotype and their role in thrombin generation, Cytometry B Clin. Cytom. 80 (1) (2011) 57–63. [32] O. Aras, A. Shet, R.R. Bach, J.L. Hysjulien, A. Slungaard, R.P. Hebbel, G. Escolar, B. Jilma, N.S. Key, Induction of microparticle- and cell-associated intravascular tissue factor in human endotoxemia, Blood 103 (12) (2004) 4545–4553. [33] I. Del Conde, C.N. Shrimpton, P. Thiagarajan, J.A. Lopez, Tissue-factor-bearing microvesicles arise from lipid rafts and fuse with activated platelets to initiate coagulation, Blood 106 (5) (2005) 1604–1611. [34] A. Tesse, M.C. Martinez, B. Hugel, K. Chalupsky, C.D. Muller, F. Meziani, D. MitoloChieppa, J.M. Freyssinet, R. Andriantsitohaina, Upregulation of proinflammatory proteins through NF-kappaB pathway by shed membrane microparticles results in vascular hyporeactivity, Arterioscler. Thromb. Vasc. Biol. 25 (12) (2005) 2522–2527.

Z. He et al. / Thrombosis Research 154 (2017) 19–25 [35] A. Angelillo-Scherrer, Leukocyte-derived microparticles in vascular homeostasis, Circ. Res. 110 (2) (2012) 356–369. [36] G. Sarlon-Bartoli, Y. Bennis, R. Lacroix, M.D. Piercecchi-Marti, M.A. Bartoli, L. Arnaud, J. Mancini, A. Boudes, E. Sarlon, B. Thevenin, A.S. Leroyer, C. Squarcioni, P.E. Magnan, F. Dignat-George, F. Sabatier, Plasmatic level of leukocyte-derived microparticles is associated with unstable plaque in asymptomatic patients with high-grade carotid stenosis, J. Am. Coll. Cardiol. 62 (16) (2013) 1436–1441. [37] A.K. Enjeti, L.F. Lincz, F.E. Scorgie, M. Seldon, Circulating microparticles are elevated in carriers of factor V Leiden, Thromb. Res. 126 (3) (2010) 250–253. [38] B. Zhou, J. Li, S. Chen, E. Zhou, L. Zheng, L. Zu, W. Gao, Time course of various cell origin circulating microparticles in ST-segment elevation myocardial infarction patients undergoing percutaneous transluminal coronary intervention, Exp. Ther. Med. 11 (4) (2016) 1481–1486. [39] S. Omoto, S. Nomura, A. Shouzu, M. Nishikawa, S. Fukuhara, T. Iwasaka, Detection of monocyte-derived microparticles in patients with Type II diabetes mellitus, Diabetologia 45 (4) (2002) 550–555.

25

[40] N. Satta, J.M. Freyssinet, F. Toti, The significance of human monocyte thrombomodulin during membrane vesiculation and after stimulation by lipopolysaccharide, Br. J. Haematol. 96 (3) (1997) 534–542. [41] A. MacKenzie, H.L. Wilson, E. Kiss-Toth, S.K. Dower, R.A. North, A. Surprenant, Rapid secretion of interleukin-1beta by microvesicle shedding, Immunity 15 (5) (2001) 825–835. [42] C. Cerri, D. Chimenti, I. Conti, T. Neri, P. Paggiaro, A. Celi, Monocyte/macrophage-derived microparticles up-regulate inflammatory mediator synthesis by human airway epithelial cells, J. Immunol. 177 (3) (2006) 1975–1980. [43] T. Neri, C. Armani, A. Pegoli, C. Cordazzo, Y. Carmazzi, S. Brunelleschi, C. Bardelli, M.C. Breschi, P. Paggiaro, A. Celi, Role of NF-kappaB and PPAR-gamma in lung inflammation induced by monocyte-derived microparticles, Eur. Respir. J. 37 (6) (2011) 1494–1502.