Platelet activation is associated with hypoadiponectinemia and carotid atherosclerosis

Atherosclerosis 188 (2006) 190–195

Platelet activation is associated with hypoadiponectinemia and carotid atherosclerosis Takuhito Shoji a , Hidenori Koyama a,∗ , Shinya Fukumoto a , Takaaki Maeno a , Hisayo Yokoyama a , Kayo Shinohara a , Masanori Emoto a , Tetsuo Shoji a , Takahisa Yamane b , Masayuki Hino b , Atsushi Shioi c , Yoshiki Nishizawa a a

Department of Metabolism, Endocrinology and Molecular Medicine (Second Department of Internal Medicine), Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan b Department of Hematology, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan c Department of Cardiovascular Medicine, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan Received 2 May 2005; received in revised form 5 August 2005; accepted 18 October 2005 Available online 28 November 2005

Abstract Adiponectin, an adipokine secreted specifically from adipose tissue, has plurifunctions including antidiabetic, antiatherosclerotic, and antiinflammatory functions. Recently, platelet activation and the subsequent local inflammation have been implicated in progression of atherosclerosis. The aim of the study is to examine the interrelation among plasma adiponectin levels, platelet activation status and quantitatively determined carotid atherosclerosis. Subjects (n = 277) including 136 type 2 diabetic, 138 hypertensive, and 203 hypercholesterolemic patients participated in the study. Platelet activation was determined as percentage of polymorphonuclear cells (PMNs) or monocytes aggregated with platelets analyzed by CD41-positivity determined by whole-blood flow cytometry. PMN–platelet aggregates were significantly and positively associated with carotid atherosclerosis (intimal-medial thickness, IMT) with the interaction stronger than that of monocyte–platelet aggregates. Stepwise regression analyses revealed that PMN–platelet aggregates were the third strongest determinant of carotid IMT, with age and HbA1c stronger independent determinants. Simple and stepwise regression analyses of the factors associated with PMN–platelet aggregates revealed that HbA1c (r = 0.423), serum adiponectin levels (r = −0.289) and age (r = −0.184) were the three independent determinants. Thus, our data unveil novel link between hypoadiponectinemia and platelet activation. © 2005 Elsevier Ireland Ltd. All rights reserved. Keywords: Adiponectin; Metabolic syndrome; Leukocyte–platelet interaction; Whole-blood flow cytometry; Intima-media thickness (IMT)

1. Introduction Adiponectin, a novel adipokine which is secreted specifically from adipose tissue and is found in multimeric complexes in the circulation at relatively high levels in human subjects, has plural biofunctions, such as antidiabetic, antiatherosclerotic, and antiinflammatory functions ∗ Corresponding author. Tel.: +81 6 6645 3806/3807; fax: +81 6 6645 3808. E-mail address: [email protected] (H. Koyama).

0021-9150/$ – see front matter © 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.atherosclerosis.2005.10.034

[1]. Several in vivo or in vitro studies reported that adiponectin inhibits monocyte adhesion to endothelial cells, lipid accumulation, inhibits tumor necrosis factor-␣ production in endothelial cells, and suppresses the progression of atherosclerosis in apo E-deficient mouse [2]. In humans, several clinical studies have found that hypoadiponectinemia or adiponectin mutant is associated with obesity, insulin resistance or diabetes mellitus [3,4], and endothelial dysfunction [5]. As well patients with hypoadiponectinemia are at a higher risk of cardiovascular death or myocardial infarction [6,7].

T. Shoji et al. / Atherosclerosis 188 (2006) 190–195

It was shown that activated platelets were found in the circulating blood of patients with coronary artery diseases [8–11]. The platelet activation appears not simply due to the results of vascular damage, since inhibition of platelet activation profoundly suppresses the progression of atherosclerosis in apo E-deficient mice [12–14]. We have also shown in a human study that platelet P-selectin expression, a marker of platelet activation, is positively associated with atherosclerotic wall thickness in carotid artery [15]. Activated platelets can bind and form aggregates with leukocytes, resulting in alteration of various leukocyte functions and inflammation (reviewed in [16]). Recently, platelet activation is also shown to be associated with insulin resistance [17,18]. Together with the close relation of adiponectin with insulin resistance and atherosclerosis, there could be a potential link between platelet activation and hypoadiponectinemia. However, interrelations between plasma adiponectin, platelet activation and atherosclerosis have not been examined yet. In the present study, we measured leukocyte–platelet aggregates, a wellestablished marker of platelet activation, in 277 subjects, and examined their associations with plasma adiponectin and carotid atherosclerosis. Our results show for the first time that leukocyte–platelet aggregates, particularly polymorphonuclear leukocyte (PMN)–platelet aggregates, are associated both with hypoadiponectinenia and carotid atherosclerosis with their interactions independent of other clinical factors.

2. Methods 2.1. Study subjects This study was approved by the Ethical Committee at Osaka City University Graduate School of Medicine (approval no. 307), and informed consent was obtained from all subjects enrolled in the study. Subjects (n = 277; 136 male and 141 female) were participants of a medical check program performed at the Diabetes Center in Osaka City University Hospital (Osaka, Japan) and the Osaka Health Promotion Center (Osaka, Japan). Clinical characteristics are summarized in Table 1. About 136 subjects were diagnosed as having type 2 diabetes, as defined by the criteria proposed by American Diabetes Association: fasting plasma glucose > 126 mg/dL (7 mmol/L), casual plasma glucose > 200 mg/dL (11.1 mmol/L), or 2 h plasma glucose > 200 mg/dL during 75 g oral glucose tolerance test, or previous therapy for diabetes. Hypertension was defined as a blood pressure higher than 140/90 mmHg or the use of agents for the treatment of hypertension. Hypercholesterolemia was defined as total cholesterol higher than 5.2 mmol/L or the use of any drugs for the treatment. In this study, type 1 diabetic subjects or the subjects treated with insulin or antiplatelet drugs were excluded.

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Table 1 Clinical characteristics of the subjects Number Age (years) Gender (M/F) Body mass index (kg/m2 ) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Smoking index (cigarette-years) Fasting plasma glucose (mmol/L) HbA1c (%) Non-HDL cholesterol (mmol/L) HDL cholesterol (mmol/L) HOMAa hsCRP (ng/mL)a Adiponectin (␮g/mL)a Diabetes Hypertension Hypercholesterolemia Monocyte–platelet (%)a PMN–platelet(%)a

277 60.4 ± 9.8 136/141 23.8 ± 3.5 130.6 ± 18.9 77.9 ± 11.2 325 ± 639 7.0 ± 1.9 6.5 ± 2.0 4.13 ± 1.07 1.44 ± 0.46 1.54 518 7.1 136 (49.1%) 138 (49.8%) 203 (73.6%) 6.1 4.5

hsCRP: high sensitivity C-reactive protein, PMN: polymorphonuclear leukocyte. Subjects treated with anti-platelet drugs or insulin were excluded from the study. Data are shown as mean ± S.D. or mediana .

2.2. Measurement of PMN- or monocyte–platelet aggregates PMN–platelet or monocyte–platelet aggregates were analyzed by whole-blood flow cytometry (Becton–Dickinson FACSCalibur, Franklin Lakes, NJ, USA) essentially as described previously [11]. In brief, peripheral blood samples were collected in 0.313% sodium citrate and were fixed in 1.0% formaldehyde/PBS for 30 min at 4 ◦ C. Then samples were diluted 4.6-fold with distilled water to lyse the erythrocytes. After the cells were washed twice with flow cytometry buffer (0.2% bovine serum albumin, 0.1% sodium azide/PBS), the cells were stained with PE-anti-CD41 antibody as a platelet identifier. The percentage of leukocyte–platelet aggregates was identified in single parameter histograms of anti-CD41-PE fluorescence displaying events from the monocyte or PMN gate. The positive analysis region was determined using a PE-conjugated IgG isotypic control. These antibodies were purchased from Beckman Coulter, Inc. (Fullerton, CA, USA). Intra- or inter-assay coefficient of variation (CV) for the measurements of PMN–platelet aggregates was 11.1% or 15.6%, respectively. Similarly, CVs for the measurements of monocyte–platelet aggregates were 11.7% for intra-assay and 10.7% for inter-assay, respectively. 2.3. Ultrasonography Ultrasonographic scanning of the carotid artery was performed by an ultrasonic phase-locked echotracking system, which was equipped with a high-resolution real-time 10 MHz liner scanner (SSD 650 CL, Aloka Co Ltd). The site of the most advanced atherosclerotic lesion was examined in the

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T. Shoji et al. / Atherosclerosis 188 (2006) 190–195

longitudinal and transverse projections to record the maximum intima-media thickness (IMT) [15].

Table 2 Simple regression analysis of the associations between carotid IMT and clinical parameters All

2.4. Biochemical analyses Plasma adiponectin levels were measured using an enzyme-linked immunosorbent assay kit (Otsuka Pharmaceuticals, Tokyo) [19]. Plasma high sensitivity C-reactive protein (hsCRP) levels were measured by N high sensitivity CRP kit obtained from Dade Behring (Marburg, Germany). Serum levels of creatinine, total cholesterol, and HDL cholesterol were measured by enzymatic methods adapted to an autoanalyzer (Hitachi 7470; Hitachi, Tokyo, Japan). Non-HDL cholesterol was calculated by subtracting HDL cholesterol from total cholesterol. Plasma glucose levels were measured by the glucose oxidation method and hemoglobin A1c (HbA1c) by high pressure liquid chromatography (normal range, 4.0–5.8%). The homeostasis Model Assessment (HOMA) index, an insulin resistance index (IR), was calculated as (fasting plasma insulin; ␮U/mL) × (fasting plasma glucose; mmol/L)/22.5 [20].

Number Age Body mass index Systolic blood pressure Diastolic blood pressure Smoking index Fasting plasma glucose HbA1c HOMAa Non-HDL cholesterol HDL cholesterol hsCRPa adiponectina PMN–platelet aggregates Monocyte–platelet-aggregates

277 0.342** −0.063 0.315** 0.059 0.153* 0.295** 0.400** 0.178** 0.004 −0.151* 0.086 −0.019 0.277** 0.183**

Male 136 0.456** −0.203* 0.264** −0.026 0.132 0.369** 0.443** 0.127 −0.046 −0.110 0.050 0.033 0.247** 0.192*

Female 141 0.254** 0.040 0.383** 0.136 0.085 0.162 0.296** 0.243** 0.123 −0.135 0.114 0.046 0.302** 0.166*

HOMA: homeostasis model assessment, HDL: high density lipoprotein, hsCRP: high sensitivity C-reactive protein. * p < 0.05. ** p < 0.01. a Logarithm-transformed value was used for analyses.

2.5. Statistical analyses Statistical analyses were performed with the use of StatView V software (SAS Institute, Cary, NC, USA). For parameters with skewed distribution (leukocyte–platelet aggregates, HOMA, plasma adiponectin or hsCRP), the data are represented as median, and non–parametric analysis (Mann–Whitney U-test) was performed for comparisons between groups. For simple or stepwise multiple regression analyses, logarithm-transformation of HOMA, plasma adiponectin or hsCRP was performed to achieve normal distribution. p < 0.05 was considered significant.

3. Results 3.1. Leukocyte–platelet aggregates and carotid atherosclerosis We first examined the association of leukocyte–platelet aggregates with atherosclerotic arterial wall thickness (IMT) of the carotid artery. Both PMN- and monocyte–platelet aggregates significantly and positively correlated with IMT of the carotid artery (Table 2). Although PMNand monocyte–platelet aggregates are closely correlated (Fig. 1A), coefficients of correlation between PMN–platelet aggregates and carotid IMT was higher than that for monocyte–platelet aggregates. When the subjects were divided into the quartile groups based on the percentages of PMN aggregated with platelets (0–2.0%: n = 65, 2.1–4.5%: n = 70, 4.6–7.0%: n = 71, 7.1%–: n = 71), the 3rd and the 4th quartiles showed significantly larger carotid IMT than the lowest quartile (Fig. 1B). Besides leukocyte–platelet aggregates, age, systolic blood pressure, smoking index, fasting

Fig. 1. (A) Strong correlation between PMN–platelet and monocyte–platelet aggregates. (B) Levels of quantitatively determined carotid atherosclerosis in quartile categorized group of PMN–platelet aggregates. Closed circles with error bars represent mean ± standard deviation. * : p < 0.05 vs. the first quartile (0–2.0%), ANOVA with multiple comparison (Scheffe’s type).

T. Shoji et al. / Atherosclerosis 188 (2006) 190–195

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Table 3 Stepwise regression analyses of clinical factors affecting carotid IMT β-values

F-values

0.370 0.291 0.160 0.156 −0.148

49.31 28.53 8.76 9.20 8.13

subjectsa

(A) All Age HbA1c PMN–platelet aggregates Systolic blood pressure Gender (male = 0, female = 1) R2 (B) Male Age HbA1c R2 (C) Female subjectsb Systolic blood pressure Age PMN–platelet aggregates R2

0.355

p < 0.0001

0.450 0.437

44.79 42.24

0.399

p < 0.0001

0.302 0.259 0.206

14.74 11.29 6.71

0.231

p < 0.0001

subjectsb

a

Variables include age, gender, smoking index, systolic blood pressure, non-HDL cholesterol, HDL-cholesterol, HbA1c, HOMA1 , hsCRP1 , adiponectin1 and PMN–platelet aggregates (0: low half, 1: high half). 1 Logarithm-transformed value was used for analyses. F value > 4.0 was considered significant. β: standard regression coefficients. b Variables include age, smoking index, systolic blood pressure, non-HDL cholesterol, HDL-cholesterol, HbA1c, HOMA1 , hsCRP1 , adiponectin1 and PMN–platelet aggregates quadruplets (0: low half, 1: high half). 1 Logarithmtransformed value was used for analyses. F value > 4.0 was considered significant. β: standard regression coefficients.

plasma glucose, HbA1c and HOMA positively, while HDL cholesterol negatively correlated with carotid IMT (Table 2). Male subjects (1.14 ± 0.58, mean ± S.D., p = 0.027) have higher carotid IMT than female subjects (1.02 ± 0.41). Even when the analyses were done in gender-separated subgroups, leukocyte–platelet aggregates showed significant positive correlation with carotid IMT, with the association of PMN–platelet aggregates with IMT stronger than that of monocyte–platelet aggregates (Table 2). Similarly, in the categorical analyses based on the proportion of PMN–platelet aggregates, the 3rd and the 4th quartile groups showed significantly higher IMT than the 1st quartile group both in male and female subgroups (Fig. 1B). In this study, neither plasma adiponectin nor hsCRP significantly correlated with carotid IMT. To examine if the association of PMN–platelet aggregates with carotid IMT is independent of the other clinical parameters, stepwise regression analyses were performed (Table 3). When age, gender, smoking index, systolic blood pressure, non-HDL cholesterol, HDL-cholesterol, HbA1c, HOMA, hsCRP, adiponectin and PMN–platelet aggregates (low half = 0, and high half = 1) were used as variables, PMN–platelet aggregates were found to be the third strongest determinant of carotid IMT along with age, HbA1c, systolic blood pressure and gender (Table 3(A)). Interestingly, when the similar analyses were performed in gender-separated subgroups (Table 3(B) and (C)), the independent association of

Fig. 2. Platelet activation determined as PMN–platelet aggregates inversely associates with plasma adiponectin levels, while positively with high sensitivity CRP.

PMN–platelet aggregates with IMT was observed only in female subgroups. In all subjects, when a model includes monocyte–platelet aggregates (low half = 0, and high half = 1) replacing PMN–platelet aggregates as variables (R2 = 0.348, p < 0.0001), monocyte–platelet aggregates were the fifth factor (β = 0.129) independently associated with carotid IMT along with age (β = 0.366), HbA1c (β = 0.314), systolic blood pressure (β = 0.158) and gender (β = −0.154). Thus, association of PMN–platelet aggregates with carotid atherosclerosis could be stronger than that of monocyte–platelet aggregates. Table 4 (A) Simple regression analyses of the factors associated with leukocyte–platelet aggregates, (B) Stepwise regression analyses associated with logarithm-transformed PMN–platelet aggregates

(A) Simple regression analyses Age Smoking index Body mass index Systolic blood pressure Diastolic blood pressure Fasting plasma glucose HbA1c Non-HDL cholesterol HDL cholesterol Log(HOMA) Log(hsCRP) Log(APN)

PMN

Monocyte

−0.184** 0.079 0.281** 0.076 0.015 0.249** 0.423** 0.007 −0.284** 0.285** 0.205** −0.289**

−0.152* 0.060 0.205** 0.051 0.029 0.162** 0.292** 0.038 −0.231** 0.211 0.168* −0.211**

β-values (B) Stepwise regression analysesa HbA1c 0.342 Age −0.154 Log(APN) −0.135 R2

0.225

F-values 44.31 8.06 5.56 p < 0.0001

R values are shown. * p < 0.05. ** p < 0.01. a Variables include age, gender, smoking index, systolic blood pressure, non-HDL cholesterol, HDL-cholesterol, HbA1c, log(HOMA), log(hsCRP) and log(APN). F-value > 4.0 was considered significant. β: Standard regression coefficients.

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3.2. Plasma adiponectin inversely associates with platelet function We next examined the association between leukocyte– platelet aggregates and plasma adiponectin. Plasma adiponectin was inversely correlated with both PMNand monocyte–platelet aggregates, with r-value for PMN stronger than monocyte (Fig. 2 and Table 4(A)). In contrast, hsCRP was positively associated with both PMNand monocyte–platelet aggregates (Fig. 2 and Table 4(A)). As reported [21], plasma adiponectin was significantly and inversely correlated with hsCRP (r = −0.370, p < 0.0001). Other potential markers for metabolic syndrome also significantly associated with increase in leukocyte–platelet aggregates; body mass index, glycemic status, HOMA index, and low HDL-cholesterol (Table 4(A)). Male subjects (median 5.1) showed significantly (p = 0.0094) higher percentage of PMN–platelet aggregates than female (median 3.8) subjects. To further examine if the association between hypoadiponectinemia and leukocyte–platelet aggregates is independent of the other clinical factors, stepwise regression analyses were performed. When age, gender, smoking index, systolic blood pressure, non-HDL cholesterol, HDLcholesterol, HbA1c, log(HOMA), log(hsCRP) and log(APN) were used as variables, only HbA1c, age and adiponectin remained significantly associated with PMN–platelet aggregates (Table 4(B)).

4. Discussion 4.1. Adiponectin as a potential regulator of platelet function In the present study, we showed for the first time that plasma adiponectin is inversely associated with platelet activation, both PMN–platelet and monocyte-platelet aggregates, in moderate numbers of subjects (n = 277). Stepwise regression analyses showed that hypoadiponectinemia is the second strongest determinant of PMN–platelet interaction along with glycemic status, a well-known regulator of platelet activation. The prothrombic state is more recently recognized as a component of the metabolic syndrome and is characterized by increased fibrinogen and plasminogen activator inhibitor1 levels and unusual abnormalities in platelet functions [22]. Our recent report also showed that components of metabolic syndrome including body mass index, blood pressure, or low HDL-cholesterol levels, were significantly associated with platelet activation [15]. Moreover, as in good agreement with previous observations [17,18], our present data shows that platelet activation is associated with insulin resistance index, HOMA. Insulin is known as a natural antagonist of platelet hyperactivity possibly through sensitization of the platelet to PGI2 and through enhancement of endothelial generation of PGI2 and NO [22]. Thus, the defects in insulin action in

insulin resistance state could create a milieu of disordered platelet activity. Our present data implicate that hypoadiponectinemia could be a potential regulator of platelet activation. Among other components of metabolic syndrome, only hypoadiponectinemia remains significantly associated with platelet activation in stepwise regression analyses besides glycemic status. At present, it is not clear whether adiponectin directly acts on platelets or indirectly through regulating insulin resistance. In any case, an attractive hypothesis emerges that part of anti-atherogenic properties of adiponectin could be mediated through modulating platelet function. In the present study, neither hypoadiponectinemia nor hsCRP is significantly associated with carotid atherosclerosis. This may be due to the limitation of the population size in our study based on the technique using flow cytometry. hsCRP was shown to be associated with carotid atherosclerosis in large numbers of subjects within the Rotterdam study [23]. Since hsCRP shows mild association with carotid atherosclerosis in non-diabetic subjects alone (r = 0.184, p = 0.0292, n = 141), heterogenous population may also attribute to the discrepancy. It has not yet been conclusive regarding relation between hypoadiponectinemia and carotid atherosclerosis. In a study consisting of 231 type 2 diabetic subjects, Matsuda et al. showed no significant association between plasma adiponectin and carotid atherosclerosis [24], which is in good agreement with our current study. In contrast, recent report by Kojima et al. [25] showed significant positive correlation between hypoadiponectinemia and carotid atherosclerosis in 142 patients with coronary artery disease and 108 control patients. These discrepancies may be due to diversity of population where Kojima’s study consists many patients with severe atherosclerotic diseases, namely coronary artery disease. 4.2. Leukocyte–platelet interaction and atherosclerosis The recruitment of peripheral monocytes to the site of vascular damage is one of the first steps in atherogenesis and inflammation. The powerful adhesive interactions that are required for monocytes to withstand local blood flow at the vessel wall can be described as a multistep process mediated by different adhesion molecules. Recent studies have provided insight into platelet functions in inflammation and atherogenesis (see recent review in [16,26]). Wide range of molecules, present on the platelet surface and/or stored in platelet granules, are involved in the interaction of platelets with leukocytes during the vascular inflammation, and resulted in the development and progression of atherosclerosis. We have recently shown in human studies that P-selectinpositive platelets, a marker of platelet activation, are indeed associated with quantitatively measured carotid atherosclerosis [15]. In the present study, we further showed that platelet interaction with leukocytes is one of the strongest factors associated with carotid atherosclerosis. P-selectin on acti-

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vated platelets initiates their interactions with leukocytes. However, the current technique to measure P-selectin on platelet surface could underestimate the activated platelets, since it does not include platelets already aggregated with leukocytes. Moreover, degranulated platelets are known to rapidly lose surface P-selectin in vivo [27]. In contrast to the well-recognized role of monocytes, PMNs have not received much consideration in atherogenesis, despite accumulating evidence suggesting a strong link between systemic inflammation and atherosclerosis. Clinical studies have demonstrated that neutrophils are activated in patients with acute coronary syndrome [28]. Moreover, accumulation of neutrophils has been observed at the site of endothelial cell denudation at ruptured plaque [29]. In our present study, besides monocyte–platelet aggregates, PMN–platelet aggregates could be a potential predictor of carotid atherosclerosis. Together with the evidence that circulating PMN–platelet complexes represent a subpopulation of activated PMN primed for adhesion, phagocytosis and intracellular killing [30], augmented PMN interaction with platelets could have profound impact on vascular inflammation and atherogenesis.

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Acknowledgements [19]

We thank Dr. Fumihiko Hato, Osaka City University, for the technical help with flow cytometry. This study was supported in part by Grant-in-Aid for scientific research (15590953 to H.K) from the Japan Society for the Promotion of Science.

[20]

[21]

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