© 1997 American Heart Association, Inc.
Articles |
Megakaryocyte Ploidy and Platelet Changes in Human Diabetes and Atherosclerosis
From the Departments of Cardiology (A.S.B., A. de B.), Medicine (Y.H., M.E., J.F.M.), and Biochemistry (J.B., R.S.), King's College School of Medicine and Dentistry; the London School of Hygiene and Tropical Medicine, Medical Statistics Unit (H.B.); and the Cruciform Project (J.F.M., J.D.E.), London, UK.
Correspondence to Adam de Belder, Department of Cardiology, King's College School of Medicine and Dentistry; Bessemer Road, London SE5 9PJ, UK.
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Abstract |
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Abstract Altered platelet morphology and function have been reported in patients with diabetes. They are likely to be associated with the pathological processes and increased risk of vascular disease seen in these patients. Mean platelet volume (MPV), platelet count, and megakaryocyte (MK) ploidy (DNA content) were measured in (1) nondiabetics with normal coronary arteries, (2) nondiabetics with coronary artery atherosclerosis, (3) diabetics without evidence of vascular complications, and (4) diabetics with vascular disease. The platelet count (±SD) was increased in all groups but only significantly in the diabetics with vascular disease (236±65 versus 250±54 versus 257±64 versus 295±90 [P
.05]x109/L, for groups I, II, III, and IV, respectively). The MPV was significantly increased in patients with atherosclerosis (7.0±0.4 versus 8.0±1.2 [P.05] versus 7.2±0.9 versus 8.1±0.9 [P.05] fL). Geometric mean MK ploidy was significantly increased in all groups compared with controls (16±1.5 versus 18.7±1.8 [P.05] versus 19.8±1.6 [P.05] versus 20.1±2.7 [P.05]). Furthermore, some patients with vascular disease and/or diabetes had a modal ploidy shift from 16 (the normal mammalian modal ploidy) to 32, with a concomitant reduction of MKs in the 8 and 16 ploidy classes. This shift was seen particularly in the diabetics with vascular disease (P=.007). Interleukin-6 (IL-6) levels were measured and were elevated in patients with atherosclerosis; the highest levels were found in the diabetic patients (0.7±0.9 versus 5.3±5.5 [P.05] versus 2.5±2.8 versus 6.7±5.5 [P.05] ng/L). In the diabetic patients with atherosclerosis, fibrinogen levels were also increased (2.85±0.76 versus 3.34±1.32 versus 2.43±1.50 versus 5.59±1.72 [P.05] g/L). Furthermore, IL-6 levels correlated with MK ploidy (r=.45, P=.009) and fibrinogen levels (r=.5, P=.0001). This study demonstrates that patients with vascular disease, particularly diabetics, have an altered MK ploidy distribution, showing a shift toward higher ploidy in association with an increased platelet mass (countxvolume). Changes in platelets in diabetes probably reflect MK changes, which themselves are a response to systemic change.
Key Words: platelet • megakaryocyte • fibrinogen • atherosclerosis • diabetes • interleukin-6
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Introduction |
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Platelets are heterogeneous in size, density, and reactivity, these changes arising at or before thrombopoiesis.1 2 Changes in these variables may be involved in the natural history of vascular disease. Larger and functionally more reactive platelets have been found after myocardial infarction3 and in diabetics.4 5 Furthermore, a raised MPV has been found to be a powerful predictor of a second infarction or sudden cardiac death when measured 6 months after initial infarction.6 Such findings led to speculation that an increased MPV may be causally related to coronary artery thrombosis and therefore to the increased risk of cardiovascular disease in diabetes.
Differences in platelet morphology and physiology are determined primarily during or before the fragmentation of their precursor cell, the MK.7 8 9 10 The process of MK differentiation and platelet production is controlled by humoral factors produced in response to platelet consumption or destruction.11 A distinctive and unique feature of MK development is the process of nuclear polyploidization. During terminal differentiation, before cytoplasmic fragmentation takes place, MKs undergo a variable number of endomitotic cycles and become polyploid.12 The ploidy of normal bone marrow MKs usually ranges from 4 to 64, with 16 being the normal modal ploidy in all mammals.12 Ploidy distribution may change physiologically as a consequence of changes in platelet demand.13 14 In addition, ploidy changes may occur under nonphysiological conditions, as shown in patients with malignant tumors.15 16
The precise biological significance of MK ploidy is not known and is the subject of much debate. Even though ploidy and platelet volume are independent variables,17 alterations in these parameters nearly always occur in tandem, the platelet volume change being an effect of change in MK cytoplasm or fragmentation. It has been suggested that an increase in MK ploidy associated with the production of large, hyperactive platelets may play a role in vascular disease.17 Thus, we studied the patterns of ploidy distribution in four groups of patients: nondiabetics and diabetics with and without atherosclerosis. The relationship between changes in ploidy and platelet counts and volume distributions was also assessed. We also measured levels of IL-6, since this cytokine has a role in MK growth and differentiation in vitro and increases MK ploidy and platelet number in vivo.18 19 20
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Methods |
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Subjects
Sixty-three patients were enrolled after fully informed consent had been obtained in accordance with the hospital ethics committee regulations. Patients with a history of angina or electrocardiographic evidence of ischemia were assessed by coronary angiography. Patients with symptoms of peripheral vascular disease and a brachial/popliteal pressure index of <1 (measured on a 5-Hz hand-held Huntleigh Doppler probe) underwent peripheral angiography. Fundoscopy was performed in all diabetics and any retinopathy noted. Renal function was assessed by measurement of creatinine and electrolytes and any proteinuria noted. Patients with any evidence of infection or renal failure were excluded. After the initial examination, patients were divided into four groups. Nondiabetic patients admitted for routine aortic or mitral valve replacement with normal coronary arteries acted as the control group (I). Nondiabetics with coronary artery disease diagnosed by coronary angiography formed group II. Diabetics with no evidence of retinopathy, peripheral vascular disease, or coronary artery disease formed group III, and diabetics with peripheral vascular disease and/or coronary artery disease diagnosed by angiography formed group IV.
Measurement of Platelet Count and MPV
Uncuffed venous blood specimens were drawn through a 21-gauge needle into a polypropylene syringe containing 0.1 vol trisodium citrate (38 g/L-1) supplemented with 1 mmol/L PGE1 (Sigma Chemical Co). After gentle mixing, the sample was placed in a 15-mL Falcon centrifuge tube and the blood centrifuged at 190g for 20 minutes at room temperature and the platelet-rich plasma collected. Platelet volume measurement was performed 1 hour after sampling on a Coulter ZN particle counter attached to a Channalyser 360 microprocessor and Apple VDU as described previously.21 An additional sample of blood was collected into EDTA and the whole-blood platelet count measured on a Coulter STKR A, which was calibrated daily. Platelet mass was calculated by multiplying platelet count by volume.
Measurement of Blood Biochemistry
Blood cholesterol, triglycerides, glucose, and creatinine were measured by photometric methods using a multichannel, random-access biochemical analyzer (Technicon Dax 48). Electrolytes were also measured on this analyzer using ion-selective electrodes. Glycosylated hemoglobin (HBAIc) was measured using an Abbott Vision analyzer (Abbott Diagnostics; reference range for nondiabetic subjects, 4.1% to 6.0%).
Fractionation of Bone Marrow Cells
Four milliliters of bone marrow was aspirated from the posterior iliac crest into sterile plastic syringes containing 1 mL of ACD-A (38 mmol/L citric acid, 75 mmol/L trisodium citrate, 139 mmol/L D-glucose) supplemented with 25 mmol/L EDTA and 28 mmol/L PGE1. The sample was diluted at room temperature with 1 vol Ca2+/Mg2+-free phosphate-buffered saline containing 3% BSA (fraction V, Sigma), 5.5 mmol/L D-glucose, 10.2 mmol/L trisodium citrate, and 2.8 mmol/L PGE1, pH 7.3 and osmolarity of 295±5 mosm/L (MK buffer). The suspension was gently pipetted and then filtered through a 150-mm mesh monofilament nylon filter (Baltex, G. Bopp & Co Ltd).
MK enrichment was performed using colloidal PVP-coated silica (Percoll, Sigma) discontinuous density-gradient fractionation. Aliquots of 5 mL bone marrow suspension were layered over 5 mL of Percoll (d=1.060 g/mL) in 15 mL Falcon centrifuge tubes, overlayered with 3 mL MK buffer containing 0.3% BSA, and centrifuged at 400g for 20 minutes at room temperature. After centrifugation, the upper layer was aspirated and discarded, and the middle layer including all the light-density cells at the interface between this layer and the Percoll were collected. These cells were then diluted with 2 vol MK buffer and centrifuged at 300g for 10 minutes at 4°C. The washing step was repeated and the sample centrifuged at 250g for 7 minutes at 4°C. The pellet was finally resuspended in MK buffer at a concentration of 1 to 2x107 cells per milliliter. From an initial bone marrow aspirate containing 
1x108 nucleated cells with an MK frequency of 0.05%, the procedure outlined above yields about 5x104 MKs with a purity of 1.5%.
MK Labeling and Flow Cytometry
Cells (1 to 2x107) were incubated in 1 mL MK buffer with a 1:20 dilution of FITC-conjugated Y2/51 anti-human GPIIIa monoclonal antibody (Dako) for 45 minutes. An isotype-matched FITC-conjugated antibody raised against A. niger glucose oxidase (Dako) was used as a negative control. Subsequently, the cells were washed with ice-cold PBS and centrifuged at 200g for 5 minutes. The cells were then resuspended with 1 mL of 0.5% paraformaldehyde in PBS and kept on ice for 1 hour. The paraformaldehyde was diluted with 5 vol cold PBS, and the cells were centrifuged at 200g for 5 minutes. The pellets were finally resuspended in 1 mL of DNA staining solution (PBS containing 0.2% BSA, 2 mmol/L MgCl2, 0.05% saponin, 0.05 mg/mL propidium iodide [Molecular Probes Inc], and 10 U/mL RNAse A) and left overnight in the dark. All the procedures described above were performed at 4°C.
Cells were analyzed with a FACScan flow cytometer (Becton Dickinson) connected to a Consort 32 computer system. Data were recorded and analyzed using the LYSYS II software program (Becton Dickinson). The instrument was set for the measurements of forward and side scatter and for the red and green fluorescence of each cell. The fluidics rate was set on low (to collect about 500 cells per second) to reduce MK activation and optimize resolution. The analyzer threshold was adjusted on the FL2 channel to exclude subcellular debris and to include all cells with a DNA content of 2 or greater. Overlaps between emitting spectra were electronically corrected. Cells stained with propidium iodide alone were used to correct for spillage of the red fluorescence signal into the green fluorescence detector. The sample stained with the two fluorochromes was used to correct the spillage of green fluorescence into the red fluorescence detector. This was done by aligning parallel to the FL-1 axis all the cells with different levels of green fluorescence within the 4-ploidy subset. A green fluorescence acquisition gate was set above the level of nonspecific fluorescence (derived from the analysis of cells stained with the irrelevant antibody) so that only data on the specifically stained cell population were acquired. In each sample, data from at least 10 000 cells were recorded in list mode. This corresponded to the running of at least 500 000 cells. After data acquisition, all samples were analyzed together. A two-parameter display of the green fluorescence versus forward scatter (a parameter related to cell size) was used to set the analysis gate, which included a distinct subset of the largest, most fluorescent cells (Fig 1
). Histograms were divided into compartments that approximated the different ploidy classes in terms of DNA content, using the 2- and 4-ploidy peaks of the ungated cells as internal references. Boundaries of DNA compartments were determined manually by setting markers at the nadirs between peaks. The frequency of cells in each DNA compartment was calculated by dividing the number of cells in the compartment by the total number of cells in the histogram.
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IL-6 Assay
Blood was taken into 3.15% sodium citrate and the plasma was obtained by centrifugation at 1000g for 20 minutes at 4°C. Aliquots of plasma were stored at -70°C. IL-6 levels were estimated by a solid-phase enzyme immunoassay technique using a commercially available kit (R&D Systems Europe) with a lower detection limit of 0.3 ng/L. Patients were classified as having elevated levels of IL-6 if they exceeded the mean level seen in the control cohort by >2 SD (ie, >2.5 ng/L).
Measurement of Plasma Fibrinogen
Venous blood was taken into 3.18% sodium citrate (9:1, vol/vol) and aliquots of plasma were stored at -70°C until assayed. Fibrinogen was measured by immunoturbidimetry (Incstar) using a Cobas Bio analyzer (Roche Diagnostic Systems). The manufacturer's quoted reference range was 1.7 to 4.0 g/L.
Statistical Analysis
Though there was a good correlation between the GMP and the arithmetic mean ploidy (r=.95, P=.0001; data not shown), the GMP provides a sounder estimate of the central tendency of a ploidy distribution; therefore, the GMP for each sample was calculated using the following formula: GMP=[(8n1)(16n2)(32n3)(64n4)(128n5)]1/n where n1, n2, n3, n4, and n5 are the number of MKs in the 8-, 16-, 32-, 64-, and if present 128-ploidy classes and n is the total. Since some of the 2- and 4-ploidy cells are not MKs, only cells with ploidy of 8 and above were included.
Platelet indices and mean ploidy were compared after log transformation because of unequal variances within groups and then compared using ANOVA. Modal ploidy changes were analyzed using Fisher's exact test and logistic regression analysis. Any association with proteinuria and any effect of insulin treatment on modal ploidy changes were assessed using Fisher's exact test. IL-6 concentrations were compared using a two-sample t test, and results were confirmed using a permutation test because of failure of distributional assumptions. Fibrinogen concentrations were compared using ANOVA. Correlations were calculated using Spearman's rank order. Data were analyzed using S Plus software. Two-sided probability values are given; 95% CIs were calculated where appropriate.
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Results |
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We analyzed four groups of age- and sex-matched patients; n=63 (Table 1
): group I, nondiabetics with normal coronary arteries; group II, nondiabetics with coronary artery disease; group III, diabetics without evidence of vascular complications; and group IV, diabetics with atherosclerosis. There was no significant difference in the mean duration of diabetes or glycosylated hemoglobin in the two groups of diabetic patients. Five of the non–insulin-dependent diabetics were treated with insulin. Though these patients are not shown separately in the table, they were taken into account when the effect of insulin on ploidy shift was analyzed. There were greater numbers of patients in the atherosclerotic groups (II and IV) on aspirin and who were smokers than in the control groups, but the difference between these two groups (II and IV) was not significant.
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Compared with control subjects, the platelet count was increased in all the study groups, but the difference between groups was significant only for the diabetics with atherosclerosis (P=.05). However, in a two-way ANOVA, there was only weak evidence for a relationship between platelet count and all diabetics (P=.066) and no evidence of a significant interaction with atherosclerotic status (P=.65). Platelet volume was raised in patients with atherosclerosis (P=.004); though the MPV was higher in the diabetics with atherosclerosis, there was no evidence of an interaction with diabetic status (P=.787), suggesting the increase was related to atherosclerosis alone. Platelet mass (countxvolume) was raised in patients with atherosclerosis (P=.001, adjusted for diabetic status) and in patients with diabetes (P=.04, adjusted for atherosclerotic status). However, there was no evidence of an interaction between these two groups, although this could be due to a lack of power (P=.1).
Flow cytometric analysis of MK ploidy distribution showed a modal shift in ploidy (from 16 to 32) in 11 of 30 diabetic patients (groups III and IV) and in 1 patient of 18 with atherosclerosis but not diabetes (group II). The modal ploidy was 16 in all control subjects (group I) (Table 2). The OR for diabetics having a ploidy shift was 18.9, with a wide CI (95% CI=2.28-159.1, P=.007). The Fisher statistic was 14.0, P=.0002. Adjusting for atherosclerosis had little effect on the risk of a shift for the diabetics, and there was no evidence of an interaction (P=.40). A representative flow cytometric analysis from one control patient and another from a patient with diabetes and atherosclerosis is shown in Fig 1
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Compared with controls, the geometric mean MK ploidy was raised in the other three groups (Fig 2). In a two-way ANOVA, atherosclerotic status was strongly associated with an increased geometric mean ploidy (P=.001), as was diabetic status (P.001). Furthermore, there was evidence of a significant interaction between these groups (P=.023), suggesting a synergistic effect between diabetes and atherosclerosis.
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In the diabetic patients there was a significant association between proteinuria (>1 g/L protein on three separate occasions) and the presence of a modal ploidy shift, giving an OR of 25 (95% CI=2.4-264; Fisher statistic=12.9, P=.0003). Those patients with a modal ploidy shift all had proteinuria, and although there were some patients with proteinuria with no ploidy shift, there were no patients without proteinuria that had a ploidy shift. Insulin treatment was associated with an OR of 4 of having a ploidy shift, but the large CIs including 1 (95% CI=0.84-18.8) in this small sample give little evidence of a real association. Fisher's exact test confirmed this finding (Fisher statistic=3.1, P=.07). Although those diabetics treated with insulin also had a higher mean ploidy (20.6 versus 19, P=.8), the difference was not significant.
Measurement of plasma IL-6 levels showed that this cytokine was elevated in groups II (P=.03) and IV (P.001) but not in group III. Fibrinogen levels were elevated in diabetics with atherosclerosis (group IV, P.001; Table 1). In a two-way ANOVA, this was found to be related to both atherosclerosis (P.001) and diabetes (P=.006), with evidence of a significant interaction (P=.002). In addition, there was a significant, moderate correlation between IL-6 levels and MK ploidy (r=.45, P=.009) and fibrinogen levels (r=.5, P=.0001) (Fig 3).
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Discussion |
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Excess mortality in diabetes is due predominantly to the vascular complications of the disease.22 The cause of these complications is poorly understood but may be related to platelet changes, as they play a major role both in thrombosis and perhaps atherosclerosis.23 Several clinical studies have shown that patients with diabetes have an altered population of circulating platelets compared with nondiabetics.24 The platelets are larger and more activated, expressing higher levels of the adhesion receptors GPIIb/IIIa and P-selectin.5 The reason for these changes is unclear, but it is likely that changes in the MK are in part responsible, since platelet structure and function are determined primarily in the MK.7 8 9 10 Indeed, in this study we have observed an increase in MK ploidy in diabetics and particularly those with atherosclerosis. Although similar changes were also seen in nondiabetics with atherosclerosis, in keeping with our previous results,25 in this group they were less pronounced than in diabetics with atherosclerosis.
In human thrombocytopenia and also in animal models,14 26 continuous platelet destruction leads to an increase in MK ploidy, which in turn is associated with an increase in platelet production. As platelet life span is shorter in patients with diabetes and vascular disease,27 28 it may be argued that in group IV the increase in MK ploidy results solely from the increase in platelet demand. However, the changes were greater than those seen in nondiabetics with atherosclerosis, and furthermore, in diabetic patients with no evidence of vascular disease (group III), we also observed an increase in MK ploidy (as was found in diabetic rats.). Thus, it seems likely that there is also a diabetes-specific MK response. The ploidy shift seen in diabetics is therefore probably a summation of both the effect of diabetes and atherosclerosis on the maturing bone marrow MK.29
In steady state platelet production, there is an inverse relationship between platelet count and size. In this study, control patients with atherosclerosis and diabetics with atherosclerosis had an increased platelet mass (platelet countxplatelet volume). The converse, a decreased platelet mass, has been found in patients with renal failure in association with an increased bleeding time.30 Both an increased platelet mass and a reduced bleeding time have been found after myocardial infarction.31 Since platelet mass is inversely related to the bleeding time (an in vivo measure of platelet function), the increase in both count and volume seen in this study may be prothrombotic.
The increased platelet volume seen in the diabetics in this study, when adjusted for atherosclerotic status, appears related to atherosclerosis rather than to diabetes. However, a weak relationship existed between diabetes and platelet count, consistent with the increased MK ploidy in diabetes. Since the platelet count was significantly greater in diabetes and atherosclerosis, as was the increased ploidy, it may be that in that group the increased platelet count is an effect of both atherosclerosis and diabetes acting via MK ploidy. Since higher-ploidy MKs have more cytoplasm, increases in ploidy are probably a mechanism for producing more platelets per MK. MK ploidy and platelet count on the one hand and platelet volume on the other are under independent hormonal control and may be independent risk factors for arterial thrombosis.
We have found increased levels of fibrinogen in diabetics with atherosclerosis, which may reflect the inflammatory nature of atherosclerosis, since fibrinogen is produced in the liver as part of the acute-phase response. IL-6, together with tissue necrosis factor (already found to be increased in acute diabetes29 ) and IL-1, represent the earliest detectable cytokines in the inflammatory response. We also found elevated levels of IL-6 in this group of patients. IL-6 has a variety of functions, which include supporting MK growth and differentiation in vitro and increasing MK ploidy and platelet count when infused into dogs.18 19 20 Therefore, it is reasonable to suggest that the shift in ploidy and platelet count seen in diabetes and atherosclerosis may be due in part to an increase in the circulating level of IL-6. IL-6 is only one of numerous hematopoietic growth factors that, acting in synergistic combinations, affect megakaryocytopoiesis and thrombopoiesis.11 Recently, a specific hemopoietic growth factor, c-MPL ligand, has been cloned.31 32 33 34 This factor has been shown to be a physiological regulator of megakaryocytopoiesis identical to thrombopoietin. It may be that the increased circulating levels of IL-6 seen in this study and other similar cytokines may affect megakaryocytopoiesis, in addition to the physiological regulator c-MPL ligand. Future work will determine the effect of c-MPL ligand on the MK-platelet axis in vascular disease.
We have shown that patients with atherosclerosis have an increase in the mean MK ploidy, associated with an increased platelet mass. In diabetic patients with atherosclerosis, this increase is more pronounced. As large platelets are more hemostatically active,2 35 it is likely that the observed increase in platelet size in conjunction with the elevated platelet counts increases the thrombotic potential in these patients. Since MK ploidy and platelet volume are under independent hormonal control,18 our study suggests that the controlling factors of both variables are elevated in diabetics with atherosclerosis. Since platelet volume is a major risk factor for myocardial infarction, identification of the control mechanism of platelet volume may help an understanding of the events preceding myocardial infarction.
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Selected Abbreviations and Acronyms |
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Acknowledgments |
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Angie S. Brown was a British Heart Foundation Junior Research Fellow; Adam de Belder was a British Heart Foundation Intermediate Fellow; and John F. Martin is a British Heart Foundation Professor of Cardiovascular Science.
Received April 1, 1996; accepted July 4, 1996.
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References |
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