- Email: [email protected]
Platelet indices and glucose control in type 1 and type 2 diabetes mellitus: A case-control study
Accepted Manuscript Platelet indices and glucose control in type 1 and type 2 diabetes mellitus: a case– control study F. Zaccardi, B. Rocca, A. Rizzi, A. Ciminello, L. Teofili, G. Ghirlanda, V. De Stefano, D. Pitocco PII:
S0939-4753(17)30137-0
DOI:
10.1016/j.numecd.2017.06.016
Reference:
NUMECD 1747
To appear in:
Nutrition, Metabolism and Cardiovascular Diseases
Received Date: 22 February 2017 Revised Date:
23 May 2017
Accepted Date: 27 June 2017
Please cite this article as: Zaccardi F, Rocca B, Rizzi A, Ciminello A, Teofili L, Ghirlanda G, De Stefano V, Pitocco D, Platelet indices and glucose control in type 1 and type 2 diabetes mellitus: a case–control study, Nutrition, Metabolism and Cardiovascular Diseases (2017), doi: 10.1016/j.numecd.2017.06.016. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Platelet indices and glucose control in type 1 and type 2 diabetes mellitus: a case–control study Zaccardi F 1,2
RI PT
Rocca B 3 Rizzi A 2 Ciminello A 4 Teofili L 4
SC
Ghirlanda G 2 De Stefano V 4
M AN U
Pitocco D 2
1
Diabetes Research Centre, University of Leicester, Leicester, UK Diabetes Care Unit, Catholic University School of Medicine, Rome, Italy 3 Institute of Pharmacology, Catholic University School of Medicine, Rome, Italy 4 Institute of Haematology, Catholic University School of Medicine, Rome, Italy
Corresponding Author
TE D
2
AC C
EP
Francesco Zaccardi Leicester Diabetes Centre, Leicester General Hospital Leicester, LE5 4PW, England Phone: 0116 258 4389 Email: [email protected]
Word Count: Abstract 272; Main Text 3513 Figures: 3 Tables: 1 Supplementary Material: 6 Tables, 2 Figures
Keywords: platelet count; platelet volume; platelet turnover; type 1 diabetes; type 2 diabetes; case-control Abbreviations: CGM: continuous glucose monitoring; MPV: Mean platelet volume; PLT: Platelet count; PM: Platelet mass; T1DM: Type 1 diabetes mellitus; T2DM: Type 2 diabetes mellitus; TX: Thromboxane
1
ACCEPTED MANUSCRIPT ABSTRACT Background and Aims: The relationship between platelet indices and glucose control may differ in type 1 (T1DM) and type 2 (T2DM) diabetes. We aimed to investigate differences in the mean platelet volume (MPV), platelet count, and platelet mass among patients with
RI PT
T1DM, T2DM, and healthy controls and to explore associations between these platelet indices and glucose control.
Methods and Results: 691 T1DM and 459 T2DM patients and 943 control subjects (blood
SC
donors) were included. HbA1c was measured in all subjects with diabetes and 36 T1DM patients further underwent 24h-continuous glucose monitoring to estimate short-term glucose
M AN U
control (glucose mean and standard deviation). Adjusting for age and sex, platelet count was higher and MPV lower in both T1DM and T2DM patients vs control subjects, while platelet mass (MPV x platelet count) resulted higher only in T2DM. Upon further adjustment for HbA1c, differences in platelet count and mass were respectively 19.5x10^9/L (95%CI: 9.8-
TE D
29.3; p<0.001) and 101fL/nL (12-191; p=0.027) comparing T2DM vs T1DM patients. MPV and platelet count were significantly and differently related in T2DM patients vs both T1DM and control subjects; this difference was maintained also accounting for HbA1c, age, and sex.
EP
Platelet mass and the volume-count relationship were significantly related to HbA1c only in
AC C
T1DM patients. No associations were found between platelet indices and short-term glucose control.
Conclusion: By accounting for confounders and glucose control, our data evidenced higher platelet mass and different volume-count kinetics in subjects with T2DM vs T1DM. Longterm glucose control seemed to influence platelet mass and the volume-count relationship only in T1DM subjects. These findings suggest different mechanisms behind platelet formation in T1DM and T2DM patients with long-term glycaemic control being more relevant in T1DM than T2DM.
2
ACCEPTED MANUSCRIPT INTRODUCTION Diabetes mellitus is a metabolic disorder associated with a 2-fold increase of microand macro-vascular atherothrombotic complications as compared to subjects without diabetes [1, 2]. Platelet activation is known to contribute to atherothrombosis development and acute
RI PT
major arterial events [3]. Consistently, an increased urinary thromboxane (TX)A2 excretion, a biomarker of in vivo platelet activation, was documented in type 2 diabetes mellitus (T2DM) patients with macrovascular complications already two decades ago [4]. Since then, many
SC
different platelet functional and/or morphological abnormalities have been reported in vivo, ex vivo, or in vitro in T2DM, altogether consistent with increased platelet activity and/or
M AN U
reduced antiplatelet drug responsiveness phenotypes [5]. Conversely, data on platelets in type 1 (T1)DM, are more limited. Recently, we have reported in young T1DM patients an increased TXA2 generation in vivo associated with microvascular damage [6]. Among different platelet morphological indices, a high mean volume (MPV) of
TE D
peripheral platelets is considered a marker associated with increased platelet activity in vivo, mainly related to the larger volume of newly-released platelets which display an increased pro-thrombotic activity [7]. High MPV has been associated with incident coronary heart
EP
disease events in T2DM [8] and in the general population [9]. Moreover, MPV has been
AC C
reported to independently predict a reduced pharmacological response to low dose aspirin in T2DM [10]. Consistently, a higher immature platelet fraction has been reported in T2DM patients with cardiovascular complications [11] and has been associated with macrovascular events in patients without diabetes [12]. Moreover, higher levels of immature platelets and have been associated with a reduced response to antiplatelet drugs in patients without [13, 14] and with T2DM [10]. Based on the above observations, the MPV has been often proposed as biomarker of poor outcomes and/or antiplatelet drug responsiveness in T2DM. However, not all the studies
3
ACCEPTED MANUSCRIPT have been consistent in reporting an increased MPV in T2DM vs non-T2DM subjects [1519]. In addition, platelet morphometric indices other than MPV, such as platelet count (PLT) and/or platelet distribution width have been investigated in T2DM and non-T2DM subjects, with inconsistent findings [15]. Data on platelet indices on T1DM are far more limited [20-
RI PT
22].
Under steady-state conditions of physiological magakariopoiesis, the platelet size is inversely related to the platelet count, and these parameters are inversely regulated to keep
SC
the platelet mass (PM = PLT x MPV) constant [23]. Therefore, the measure of only one morphometric platelet index might be poorly informative of the kinetics of platelet generation
M AN U
in vivo and be potentially misleading or give inconsistent findings. Furthermore, previous studies on T2DM and a single platelet morphometric index often lacked of adjustment for potential confounders known to affect MPV, PLT and PM, independently of diabetes [24], such as age, gender and ethnicity [25]. Moreover, whether and how glycaemic control can
TE D
affect the kinetics of platelet production in vivo is also unclear. Recently, high fasting glucose levels have been associated with high MPV in a large male population [24]; however, one fasting glucose measurement is poorly informative of the short- and long-term regulation of
EP
glucose metabolism or of the type of underlying metabolic defect (T1DM, T2DM, glucose
AC C
intolerance) [26]. Finally, investigating T1DM separately from T2DM is potentially relevant, since hyperglycaemia in T1DM generally does not cluster with other metabolic alterations or comorbidities as in T2DM. To help clarify these aspects, we performed a large, retrospective, case-control study
including T1DM, T2DM and healthy subjects and we investigated MPV, PLT, PM and their relationships in physiological and different diabetes conditions. We also investigated the effect of long- and short-term glucose control on the same platelet indices.
4
ACCEPTED MANUSCRIPT METHODS Population The present study is a retrospective analysis of the database from T1DM and T2DM
RI PT
subjects of the outpatient diabetes clinic of the “A. Gemelli” Hospital, Catholic University School of Medicine, Rome. For subjects with T1DM and T2DM, data collected during one calendar year (2013) were anonymously extracted from hospital datasets providing that there were information on age and sex, and HbA1c, MPV and PLT values from samples collected
SC
on the same day. In our outpatient Unit, T1DM is diagnosed as the presence of at least one of
M AN U
the diabetes-related autoantibodies (IA-2 protein tyrosine phosphatase, glutamic acid decarboxylase, or insulin antibody) in subjects needing insulin treatment and T2DM is diagnosed according to the American Diabetes Association criteria [27]. Patients with endstage renal failure and on dialysis were excluded. For the control group, we used an anonymised database including all blood donor volunteers during the same period (year
TE D
2013) and we extracted data with available information on age, gender, MPV and PLT. For the short-term glucose control study, a group of 36 uncomplicated (absence of
EP
macro- and micro-vascular disease and neuropathy) T1DM consenting patients were consecutively enrolled to undergo a 24-hour continuous glucose monitoring (CGM)
AC C
(CGMS® Guardian REAL-Time, Medtronic MiniMed, Northridge, CA, USA). The glucose sensor was inserted subcutaneously in the abdominal wall and patients were instructed to perform the required sensor calibration procedure according to manufacturer's instructions; at the end of CGM, fasting blood samples were taken to measure haemocromocitometric and biochemical variables. Resting systolic blood pressure was measured with a random-zero sphygmomanometer by a trained nurse; body mass index was computed as the ratio of weight in kilograms to the square of height in meters; waist circumference was calculated as the average of 2 measurements taken after inspiration and expiration at the midpoint between the 5
ACCEPTED MANUSCRIPT lowest rib and iliac crest; and waist-hip ratio was defined as waist girth/hip circumference measured at the trochanter major. The short-term glucose control study was approved by the
Hematological and Biochemical measurements
RI PT
institutional ethics committee and subjects signed an informed consent.
PLT and MPV were measured in K3-EDTA anticoagulated blood by an automatic blood cell cytometer (Sysmex SF-3000, Dasit, Milano, Italy). Blood samples were processed
SC
within 2 hrs after collection, according to the standard operating procedure of our Institution. In the group of patient with CGM-data, immature platelet fraction were counted by the
M AN U
Sysmex® XE-500 Instrument (Sysmex Corporation, Kobe, Japan).
HbA1c, blood glucose, and lipids were measured at the Department of Clinical Biochemistry: plasma glucose and whole blood HbA1c were measured using the hexokinase method and ion exchange high performance liquid chromatography, respectively; serum
TE D
triglyceride, high density lipoprotein cholesterol and low density lipoprotein cholesterol were measured using an Olympus auto-analyser (Olympus Corporation, Tokyo, Japan).
EP
Statistical Analysis
AC C
Given the availability of a large number of controls (blood donors) in the Institutional database, when estimating sample size the number of patients with T1DM and T2DM was considered the limiting factor. We therefore calculated the minimum number of T1DM and T2DM patients with 1:1 ratio between diabetes-specific cases and blood donors, a power of 0.9 and two-sided α=0.017 to account for multiple comparisons (T1DM vs controls; T2DM vs controls; T2DM vs T1DM). Assuming a mean MPV of 8.5 fL in controls and a common standard deviation (SD) for the three groups of 1.7 fL [15], with 400 participants per group we could detect pairwise differences of at least 0.44 fL. Similarly, assuming a mean PLT of
6
ACCEPTED MANUSCRIPT 241x103/µL in controls and a common SD of 71x103/µL [15], the same sample size allowed detecting pairwise differences of at least 18x103/µL. As no data have been reported on the relationship between platelet indices and short-term glucose control, it was not possible to perform formal sample size calculations for the short-term glucose control study.
RI PT
For all analyses, the natural logarithm-transformed of the non-normal distributed variable HbA1c was used. Descriptive data are presented as means and SD for continuous variables and number and percentages for categorical ones. Unadjusted correlation
SC
coefficients were calculated to assess the correlation between platelet indices and other continuous variables, whereas mean differences between groups were estimated for
M AN U
categorical factors. PM was calculated as MPV x PLT and expressed in fL/nL. Associations between platelet indices and other variables involved multiple linear regressions, progressively adjusted for age, sex, and HbA1c. Differences (∆) were estimated among the three groups using Bonferroni-corrected standard errors to account for multiple
TE D
comparisons. As none of the transformation allowed CGM-derived variables to be approximately normally distributed, associations with such variables were estimated using nonparametric tests. Differences in the relationship between MPV and PLT across the
EP
three groups were computed as the ratio of the difference between the coefficients
AC C
(slopes) of two groups and the coefficient of the reference group; pairwise estimations were adjusted for multiple testing and reported as percentages. All analyses were performed with Stata 14.1 (Stata Corp, College Station, TX, USA)
and results are reported with 95% confidence intervals (CIs). P-values <0.05 were considered statistically significant.
7
ACCEPTED MANUSCRIPT RESULTS Platelet indexes A total of 2,903 participants were included in the study: 691 T1DM, 459 T2DM, and
RI PT
943 control subjects; their characteristics and platelet indices are reported in Table 1. Overall, T2DM patients were slightly older than the other two groups, less females were present in the T1DM group, while the glycaemic control, as expressed by HbA1c, was similar in T1DM and T2DM groups. Unadjusted analyses showed that T2DM patients had the highest PLT and
SC
PM values among the three groups. Moreover, the analysis of the correlations between
M AN U
clinical/metabolic and platelet indexes showed that female subjects had consistently and significantly increased values of both PLT and PM in each group (p<0.001) (Supplementary Material, Table S1) while MPV was unrelated to sex. There was no association of age with any platelet index (Table S1).
After adjusting for age and sex, PLT and PM were still significantly higher in T2DM
TE D
vs. e control or T1DM groups (Figure 1). MPV resulted significantly although slightly lower in both T1DM (∆MPV -0.3 fL; 95% CI: -0.5, -0.1; p<0.001) and T2DM (-0.6 fL; -0.9, -0.4;
EP
p<0.001) vs control subjects and in T2DM vs T1DM subjects (-0.3 fL; -0.6, -0.1; p=0.007). The observation that T2DM patients had the highest PM, in spite of a slight reduction
AC C
in MPV, prompted us to investigate the relationship between MPV and PLT within each group, as expressed by the slope of the linear fitting of the values of the two indexes. As expected, there was an inverse relationship between MPV and PLT, although the type of dependency between these two variables differed among the three groups (Figure 2). In fact, the absolute value of the slope in T2DM subjects was 36% lower than in controls (95% CI: 14.4, 57.6; p<0.001) and 30.7% (7.2, 54.2; p=0.002) lower than in T1DM subjects (Table S2), At variance with T2DM, T1DM and control subjects showed superimposable slope
8
ACCEPTED MANUSCRIPT values (7.7%; -19.4, 34.7; p=0.5). The above results were consistent in the adjusted analyses as well (Table S2). These data overall indicate a smaller reduction of MPV as a function of increasing
RI PT
PLT values in T2DM as compared to the other two groups.
Long-term glucose control
Differences in platelet indexes were then analysed by adjusting for HbA1c in addition
SC
to age and sex, only in subjects with diabetes. After adjusting for HbA1c, PLT and PM remained higher in T2DM vs. T1DM, while MPV remained lower: ∆PLT, ∆PM and ∆MPV
M AN U
were respectively 19.5 x 10^9/L (95% CI: 9.8, 29.3; p<0.001), 101 fL/nL (12, 191; p=0.027) and -0.3 fL (-0.6, -0.1; p=0.003) (Figure 1). Moreover, after adjusting for HbA1c also the absolute value of the slope of the inverse relationship between MPV and PLT remained 33.4% (95% CI: 8.7, 58.1; p=0.001) significantly lower in T2DM than T1DM subjects (Table
TE D
S2).
HbA1c positively correlated with PLT and PM in T1DM, while it correlated only with PM in T2DM (Table S1). Given this association, we then investigated the distribution of age
EP
and sex-adjusted platelet indices according to quartiles of HbA1c. In the T1DM group there
AC C
was a progressive, concentration-depend increase of PLT and PM from the lowest to the highest HbA1c quartile (Figure 3). At variance with T1DM, T2DM showed non-significant trends for PM, MPV and PLT across the HbA1c quartiles (Figure 3). Given the influence of HbA1c on PM in T1DM, we then analysed the effect of
HbA1c on the relationship between MPV and PLT across the HbA1c quartiles. In T1DM, the absolute slope value was 41.1% (95% CI: 14.3, 67.8; p=0.003) significantly smaller in patients in the highest HbA1c quartile as compared to the lowest quartile (Figure S1 and Table S3). No differences in slopes were observed across the extreme HbA1c quartiles in
9
ACCEPTED MANUSCRIPT T2DM (37.6%; -10.5, 85.3; p=0.1), consistently with the lack of association with PM. Results were similar in adjusted analyses (Table S3).
Short-term glucose control
RI PT
Clinical, metabolic, and CGM-derived data in 36 uncomplicated T1DM subjects are reported in Table S4 and Figure S2. The median age and diabetes duration were 35 (interquartile range: 27-42) and 14 (8-24) years, respectively. CGM-median glucose was 123
SC
(interquartile range: 104-160) mg/dl, glucose coefficient of variation 28% (22-40) and HbA1c 7.0% (6.5-7.8).
M AN U
Table S5 shows correlation coefficients between platelet indices and CGM-derived glucose variables. No association was found for each platelet index with GM, GSD, or coefficient of variation of 24-hour glucose values. Given the small sample size, other clinical/metabolic characteristics and correlations are reported as explorative data in Table S4
AC C
EP
TE D
and Table S6, respectively.
10
ACCEPTED MANUSCRIPT DISCUSSION To our knowledge, this is the first study which considered together different platelet indexes and their relationships, in large cohorts of T1DM, T2DM and healthy
RI PT
subjects. Data on age and sex allowed the estimation of differences accounting for these important confounders; moreover, HbA1c and 24-hour glucose data, along with an accurate diabetes phenotyping, helped elucidating the role of short and long term glucose control and differentiate its impact on platelet generation in T1DM and T2DM.
SC
In fact, most of previous studies investigating differences in platelet
M AN U
morphometric indexes in diabetes usually considered a single parameter with few exceptions [16, 28, 29] and did not study the relationship between PLT and MPV, which is an indirect index of megakariopoiesis in vivo. Moreover, potential confounders were not considered, virtually only T2DM subjects were included, or control groups were heterogeneous (i.e., general population, non-T2DM patients with chronic cardiovascular
TE D
disease or acute medical conditions) [15]. These limitations have so far blurred the possibility to clarify the presence and extent of the possible differences in platelet
EP
indexes in T1DM and T2DM, their relationships, and the relative importance of glucose control both at short- and long-term. Our study attempted to overcome these limitations.
AC C
We investigated MPV and PLT, their product (PM), and their relationship, because one or even two parameters without studying their relationship scarcely reflect the kinetics of in vivo platelet generation. Complex feedback mechanisms converging to the bone marrow megakaryocytes operate to maintain constant the PM under normal conditions [30], with an inverse relationship between platelet volume and count [31]. In some clinical settings, the platelet mass has been demonstrated to be a reliable index of thrombopoiesis [32, 33]. Abnormal megakaryopoietic mechanisms and increased platelet turnover have been often hypothesized for T2DM [34]. However, studies on primary 11
ACCEPTED MANUSCRIPT megakaryocytes in vivo are hardly feasible in patients with non-haematological diseases, such as diabetes. Thus the study of the PM and the relationship of MPV and PLT might be particularly helpful in this context. Our findings indicated that T2DM is characterized by a significant increase of
RI PT
PM, largely driven by a changed inverse relationship between PLT and MPV, whereby the increase in PLT was associated with a reduced proportional decrease in MPV. This feature characterised T2DM only as it was not observed in T1DM which showed a PLT-
SC
MPV relationship similar to healthy subjects. Overall these data indicate different kinetic mechanism(s) regulating platelet production in T2DM vs both normal subjects and
M AN U
T1DM. Of note, this characteristic remained after adjusting for potential confounders such as age, sex and, more importantly, HbA1c. Furthermore, in T2DM this different relationship between MPV and PLT appeared not influenced by HbA1c levels. These observations may suggest that extra-glycaemic factors are possibly prevalent in
TE D
modulating platelet generation in T2DM. In addition, our data are consistent with studies in T2DM animal models indicating platelet hyper-regeneration and increased thrombotic risk, independently of blood glucose levels [35]. Our results are consistent with and
EP
enlarge a previous study, showing an increased megakaryocyte ploidy in the bone
AC C
marrow of subjects with diabetes [34], being nuclear ploidy a morphological marker of active platelet production. Moreover, a higher fraction of immature platelets in T2DM [11] has been associated with a reduced response to aspirin which was corrected by a more daily frequent dosing (every 12 hours) rather than by doubling the daily aspirin dose [10, 36-38] which would be consistent with a faster 24-hour platelet turnover. At variance with T2DM, platelet production mechanisms appear overall unchanged in T1DM. In spite of a higher PLT and lower MPV, nevertheless the inverse relationship between the two parameters was fully superimposable to healthy subjects,
12
ACCEPTED MANUSCRIPT with similar total PM. These results are in line with previous evidence showing normal immature platelet counts and preserved response to once-daily antiplatelet therapy in T1DM vs matched controls [6]. At variance with T2DM, T1DM patients showed a stronger and concentration-dependent, direct association between PM or MPV-PLT
RI PT
relationship with HbA1c. Moreover, the subgroup of T1DM with the worse long-term glycaemic control (mean HbA1c 9.5%) showed a significant alteration of the MPV-PLT relationship. Interestingly, in this subgroup the increase in PM appeared mainly driven by
SC
a disproportionate increase in platelet count not associated with a proportional reduction of the MPV which seemed stable across the HbA1c quartiles. An ‘osmotic’ effect of
M AN U
higher plasma glucose on platelet volume in this subgroup cannot be excluded [39]. However, we cannot also exclude that higher values of HbA1c in T1DM could impair platelet turnover to an extent similar to T2DM, acting on the central platelet production rather than on peripheral characteristics.
TE D
The differences in platelet indices and turnover possibly reflect the different pathophysiological mechanisms operating in T1DM vs T2DM [40]. In T2DM, the hyperglycaemia is more likely clustered with metabolic abnormalities related to insulin (i.e.,
hypertension,
EP
resistance
dyslipidaemia,
abdominal
obesity,
low-grade
AC C
inflammation). These abnormalities have been associated with both higher platelet activation [41, 42] and larger platelet volume [43, 44]. In particular, inflammatory mediators such as interleukin-1, interleukin-6, tumour necrosis factor alpha, or interferon gamma, are known to enhance thrombopoiesis with a shift towards the synthesis of younger, larger and prothrombotic platelets [45]. Platelet generation in T1DM and T2DM require further investigation. In the last few years short-term, rapid glucose excursions (“glycaemic variability”) have been proposed as an HbA1c-independent risk factor for vascular
13
ACCEPTED MANUSCRIPT complications [26] and associated with platelet activation [46]. To further investigate the role of glucose control independent of other potential confounders, in T1DM subjects without complications where hyperglycaemia is the only risk factor, we obtained detailed information on glucose excursions from CGM-data and platelet indices. Our result did
RI PT
not show any association between short-term glucose control parameters and platelet indices.
We should acknowledge some limitations of this study. It has been reported that
SC
MPV progressively increases when blood is collected in EDTA until 2 hours, which has been suggested as the optimal measuring time after venepuncture [47, 48]. In our study
M AN U
the time interval between collection and analysis was not recorded, but, being a singlecentre study with standardized procedures, it can be reasonably expected that the distribution of the interval between blood drawing and analysis did not differ between the study groups. Moreover, the maximum swelling of platelets in EDTA occur in the first 5
TE D
minutes, with a residual MPV increase by only 10-15% over the next 2 hours [47]. While we adjusted the analyses for well-established confounders [25, 49], other variables which could potentially influence the association between diabetes and platelet
EP
indexes (such as cardiovascular disease risk factors or treatments, micro- and
AC C
macro-vascular complications, body mass index, or glomerular filtration) were not available for the overall population. Although a clear evidence on the role of these factors as confounders or effect-modifiers is lacking [15, 24], future studies are required to evaluate whether and how such parameters contribute to the differences in platelet indexes in subjects with and without diabetes. Lastly, we did not assess the association between short-term glucose control and platelet indices in T2DM. On the other hand, strengths of our study included the accurate definition of diabetes cases which allowed a clear distinction between T1DM and T2DM, the large sample size
14
ACCEPTED MANUSCRIPT (particularly T1DM subjects), and the inclusion of controls who, by definition, had no haematological disorders which could influence megakaryopoiesis.
Conclusions and future area of research
RI PT
In this study, we included a large sample of well-defined T1DM, T2DM and healthy subjects and, accounting for suggested potential confounders [49], we investigated multiple platelet parameters and their relationship to unravel the separate
SC
role of glucose and diabetes type on platelet indexes and generation. We observed that the physiological feedback mechanisms to maintain PM were preserved in T1DM except
M AN U
for patients with poor long-term glucose control. Conversely, T2DM had consistently high PLT, PM and a different inverse relationship between the MPV and PLT, poorly influenced by glycaemic control.
Given the considerable paucity of data in T1DM and on the role of short-term
TE D
glucose control, further studies are warranted to confirm and enlarge our results. Moreover, future studies in subjects with diabetes might quantify the potential ability of platelet indices and their relationships to determine whether these indices could be
AC C
EP
potential target or indicator of the beneficial effect of therapeutic approaches [50].
15
ACCEPTED MANUSCRIPT ACKNOWLEDGMENTS AUTHOR CONTRIBUTION FZ, DP, BR study idea and design; FZ, AR, AC, LT, VDS data extraction; FZ data analysis; FZ, BR first manuscript draft. All authors provided study critical revision, draft amendments, and approved the final version to publish. FZ is the study guarantor.
RI PT
CONFLICT OF INTEREST None related to this paper for all Authors.
AC C
EP
TE D
M AN U
SC
FUNDING The study was supported by grants from: Linea D3.2 2013-70201169 to BR; and Italian Ministry for University and Research ‘Fondo per il Sostegno dei Giovani’ Anno finanziario 2012 to AR.
16
ACCEPTED MANUSCRIPT REFERENCES
AC C
EP
TE D
M AN U
SC
RI PT
[1] Emerging Risk Factors C, Seshasai SR, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. The New England journal of medicine. 2011;364:829-41. [2] Livingstone SJ, Looker HC, Hothersall EJ, Wild SH, Lindsay RS, Chalmers J, et al. Risk of cardiovascular disease and total mortality in adults with type 1 diabetes: Scottish registry linkage study. PLoS medicine. 2012;9:e1001321. [3] Davi G, Patrono C. Platelet activation and atherothrombosis. The New England journal of medicine. 2007;357:2482-94. [4] Davi G, Catalano I, Averna M, Notarbartolo A, Strano A, Ciabattoni G, et al. Thromboxane biosynthesis and platelet function in type II diabetes mellitus. The New England journal of medicine. 1990;322:1769-74. [5] Kumbhani DJ, Marso SP, Alvarez CA, McGuire DK. State-of-the-Art: Hypo-responsiveness to oral antiplatelet therapy in patients with type 2 diabetes mellitus. Current cardiovascular risk reports. 2015;9:4. [6] Zaccardi F, Rizzi A, Petrucci G, Ciaffardini F, Tanese L, Pagliaccia F, et al. In Vivo Platelet Activation and Aspirin Responsiveness in Type 1 Diabetes. Diabetes. 2016;65:503-9. [7] Martin JF, Kristensen SD, Mathur A, Grove EL, Choudry FA. The causal role of megakaryocyteplatelet hyperactivity in acute coronary syndromes. Nature reviews Cardiology. 2012;9:658-70. [8] Han JY, Choi DH, Choi SW, Kim BB, Ki YJ, Chung JW, et al. Stroke or coronary artery disease prediction from mean platelet volume in patients with type 2 diabetes mellitus. Platelets. 2013;24:401-6. [9] Klovaite J, Benn M, Yazdanyar S, Nordestgaard BG. High platelet volume and increased risk of myocardial infarction: 39,531 participants from the general population. Journal of thrombosis and haemostasis : JTH. 2011;9:49-56. [10] Rocca B, Santilli F, Pitocco D, Mucci L, Petrucci G, Vitacolonna E, et al. The recovery of platelet cyclooxygenase activity explains interindividual variability in responsiveness to low-dose aspirin in patients with and without diabetes. Journal of thrombosis and haemostasis : JTH. 2012;10:1220-30. [11] Lee EY, Kim SJ, Song YJ, Choi SJ, Song J. Immature platelet fraction in diabetes mellitus and metabolic syndrome. Thrombosis research. 2013;132:692-5. [12] Ibrahim H, Schutt RC, Hannawi B, DeLao T, Barker CM, Kleiman NS. Association of immature platelets with adverse cardiovascular outcomes. Journal of the American College of Cardiology. 2014;64:2122-9. [13] Guthikonda S, Alviar CL, Vaduganathan M, Arikan M, Tellez A, DeLao T, et al. Role of reticulated platelets and platelet size heterogeneity on platelet activity after dual antiplatelet therapy with aspirin and clopidogrel in patients with stable coronary artery disease. Journal of the American College of Cardiology. 2008;52:743-9. [14] Stratz C, Bomicke T, Younas I, Kittel A, Amann M, Valina CM, et al. Comparison of Immature Platelet Count to Established Predictors of Platelet Reactivity During Thienopyridine Therapy. Journal of the American College of Cardiology. 2016;68:286-93. [15] Zaccardi F, Rocca B, Pitocco D, Tanese L, Rizzi A, Ghirlanda G. Platelet mean volume, distribution width, and count in type 2 diabetes, impaired fasting glucose, and metabolic syndrome: a metaanalysis. Diabetes/metabolism research and reviews. 2015;31:402-10. [16] Kim JH, Kang SB, Kang JI, Kim JW, Kim SY, Bae HY. The relationship between mean platelet volume and fasting plasma glucose differs with glucose tolerance status in a Korean general population: gender differences. Platelets. 2013;24:469-73. [17] Hendra TJ, Oswald GA, Yudkin JS. Increased mean platelet volume after acute myocardial infarction relates to diabetes and to cardiac failure. Diabetes research and clinical practice. 1988;5:63-9.
17
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
[18] Abali G, Akpinar O, Soylemez N. Correlation of the coronary severity scores and mean platelet volume in diabetes mellitus. Advances in therapy. 2014;31:140-8. [19] Bavbek N, Kargili A, Kaftan O, Karakurt F, Kosar A, Akcay A. Elevated concentrations of soluble adhesion molecules and large platelets in diabetic patients: are they markers of vascular disease and diabetic nephropathy? Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. 2007;13:391-7. [20] Sterner G, Carlson J, Ekberg G. Raised platelet levels in diabetes mellitus complicated with nephropathy. Journal of internal medicine. 1998;244:437-41. [21] van der Planken MG, Vertessen FJ, Vertommen J, Engelen W, Berneman ZN, De Leeuw I. Platelet prothrombinase activity, a final pathway platelet procoagulant activity, is overexpressed in type 1 diabetes: no relationship with mean platelet volume or background retinopathy. Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. 2000;6:65-8. [22] Sharpe PC, Trinick T. Mean platelet volume in diabetes mellitus. The Quarterly journal of medicine. 1993;86:739-42. [23] Kuter DJ. Milestones in understanding platelet production: a historical overview. British journal of haematology. 2014;165:248-58. [24] Panova-Noeva M, Schulz A, Hermanns MI, Grossmann V, Pefani E, Spronk HM, et al. Sex-specific differences in genetic and nongenetic determinants of mean platelet volume: results from the Gutenberg Health Study. Blood. 2016;127:251-9. [25] Biino G, Santimone I, Minelli C, Sorice R, Frongia B, Traglia M, et al. Age- and sex-related variations in platelet count in Italy: a proposal of reference ranges based on 40987 subjects' data. PloS one. 2013;8:e54289. [26] Zaccardi F, Pitocco D, Ghirlanda G. Glycemic risk factors of diabetic vascular complications: the role of glycemic variability. Diabetes/metabolism research and reviews. 2009;25:199-207. [27] American Diabetes A. Diagnosis and classification of diabetes mellitus. Diabetes care. 2014;37 Suppl 1:S81-90. [28] Shah B, Sha D, Xie D, Mohler ER, 3rd, Berger JS. The relationship between diabetes, metabolic syndrome, and platelet activity as measured by mean platelet volume: the National Health And Nutrition Examination Survey, 1999-2004. Diabetes care. 2012;35:1074-8. [29] Verdoia M, Schaffer A, Barbieri L, Cassetti E, Nardin M, Bellomo G, et al. Diabetes, glucose control and mean platelet volume: a single-centre cohort study. Diabetes research and clinical practice. 2014;104:288-94. [30] Kaushansky K. Historical review: megakaryopoiesis and thrombopoiesis. Blood. 2008;111:981-6. [31] Bessman JD, Williams LJ, Gilmer PR, Jr. Mean platelet volume. The inverse relation of platelet size and count in normal subjects, and an artifact of other particles. American journal of clinical pathology. 1981;76:289-93. [32] Kim MJ, Park PW, Seo YH, Kim KH, Seo JY, Jeong JH, et al. Comparison of platelet parameters in thrombocytopenic patients associated with acute myeloid leukemia and primary immune thrombocytopenia. Blood coagulation & fibrinolysis : an international journal in haemostasis and thrombosis. 2014;25:221-5. [33] Gerday E, Baer VL, Lambert DK, Paul DA, Sola-Visner MC, Pysher TJ, et al. Testing platelet mass versus platelet count to guide platelet transfusions in the neonatal intensive care unit. Transfusion. 2009;49:2034-9. [34] Brown AS, Hong Y, de Belder A, Beacon H, Beeso J, Sherwood R, et al. Megakaryocyte ploidy and platelet changes in human diabetes and atherosclerosis. Arteriosclerosis, thrombosis, and vascular biology. 1997;17:802-7. [35] Hernandez Vera R, Vilahur G, Ferrer-Lorente R, Pena E, Badimon L. Platelets derived from the bone marrow of diabetic animals show dysregulated endoplasmic reticulum stress proteins that contribute to increased thrombosis. Arteriosclerosis, thrombosis, and vascular biology. 2012;32:2141-8. 18
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
[36] Bethel MA, Harrison P, Sourij H, Sun Y, Tucker L, Kennedy I, et al. Randomized controlled trial comparing impact on platelet reactivity of twice-daily with once-daily aspirin in people with Type 2 diabetes. Diabetic medicine : a journal of the British Diabetic Association. 2016;33:224-30. [37] Dillinger JG, Drissa A, Sideris G, Bal dit Sollier C, Voicu S, Manzo Silberman S, et al. Biological efficacy of twice daily aspirin in type 2 diabetic patients with coronary artery disease. American heart journal. 2012;164:600-6 e1. [38] Spectre G, Arnetz L, Ostenson CG, Brismar K, Li N, Hjemdahl P. Twice daily dosing of aspirin improves platelet inhibition in whole blood in patients with type 2 diabetes mellitus and micro- or macrovascular complications. Thrombosis and haemostasis. 2011;106:491-9. [39] Martyn CN, Matthews DM, Popp-Snijders C, Tucker J, Ewing DJ, Clarke BF. Effects of sorbinil treatment on erythrocytes and platelets of persons with diabetes. Diabetes care. 1986;9:36-9. [40] Zaccardi F, Webb DR, Yates T, Davies MJ. Pathophysiology of type 1 and type 2 diabetes mellitus: a 90-year perspective. Postgraduate medical journal. 2016;92:63-9. [41] Davi G, Guagnano MT, Ciabattoni G, Basili S, Falco A, Marinopiccoli M, et al. Platelet activation in obese women: role of inflammation and oxidant stress. Jama. 2002;288:2008-14. [42] Santilli F, Vazzana N, Liani R, Guagnano MT, Davi G. Platelet activation in obesity and metabolic syndrome. Obesity reviews : an official journal of the International Association for the Study of Obesity. 2012;13:27-42. [43] Coban E, Ozdogan M, Yazicioglu G, Akcit F. The mean platelet volume in patients with obesity. International journal of clinical practice. 2005;59:981-2. [44] Sansanayudh N, Muntham D, Yamwong S, Sritara P, Akrawichien T, Thakkinstian A. The association between mean platelet volume and cardiovascular risk factors. European journal of internal medicine. 2016;30:37-42. [45] Burstein SA, Peng J, Friese P, Wolf RF, Harrison P, Downs T, et al. Cytokine-induced alteration of platelet and hemostatic function. Stem cells. 1996;14 Suppl 1:154-62. [46] Santilli F, Formoso G, Sbraccia P, Averna M, Miccoli R, Di Fulvio P, et al. Postprandial hyperglycemia is a determinant of platelet activation in early type 2 diabetes mellitus. Journal of thrombosis and haemostasis : JTH. 2010;8:828-37. [47] Jackson SR, Carter JM. Platelet volume: laboratory measurement and clinical application. Blood reviews. 1993;7:104-13. [48] Lance MD, van Oerle R, Henskens YM, Marcus MA. Do we need time adjusted mean platelet volume measurements? Laboratory hematology : official publication of the International Society for Laboratory Hematology. 2010;16:28-31. [49] Harrison P, Goodall AH. Studies on Mean Platelet Volume (MPV) - New Editorial Policy. Platelets. 2016;27:605-6. [50] Asher E, Fefer P, Shechter M, Beigel R, Varon D, Shenkman B, et al. Increased mean platelet volume is associated with non-responsiveness to clopidogrel. Thrombosis and haemostasis. 2014;112:137-41.
19
ACCEPTED MANUSCRIPT Figure Legends Figure 1: Absolute differences in platelet count (x109/L), mean platelet volume (fL), and platelet mass (fL/nL).
RI PT
The figure depicts and reports differences (∆) with 95% confidence intervals comparing the first vs the second group, for each comparison (i.e., in age and sex adjusted analysis, platelet count was 18.7 x109/L greater and mean platelet volume 0.3 fL lower comparing Type 2 vs Type 1 diabetes patients).
Figure 2: Relationship between mean platelet volume and platelet count, by diabetes group.
M AN U
SC
The figure shows the linear fitting of mean platelet volume and platelet count. Slope and adjusted R2 were respectively: -0.0108 and 0.136 for Healthy controls; -0.0099 and 0.152 for Type 1 diabetes patients; and -0.0069 and 0.136 for Type 2 diabetes patients.
Figure 3: Relationship between platelet indices and HbA1c, by diabetes group.
AC C
EP
TE D
Platelet indices means (squares) and 95% confidence intervals (spikes) are calculated within diabetes-specific quartiles of HbA1c levels and plotted against mean HbA1c levels within each quartile. HbA1c values within brackets are geometric means and P-values indicate age and sex-adjusted p for linear trend. HbA1c [mmol/mol] = 10.9 * HbA1c [%] – 23.5.
20
Table 1: Characteristic of the subjectsACCEPTED included in the study MANUSCRIPT Controls (N=943) 41.8 (10.1) 675; 72% 231 (32) 10.3 (1.5) 2355 (513)
Variable
Type 2 Diabetes (N=459) 56.5 (17.5) 274; 60% 7.9 (2.2) 63 (24) 265 (90) 9.7 (1.7) 2522 (797)
P-value <0.001 <0.001 0.110 0.110 <0.001 <0.001 <0.001
RI PT
Age [years] Sex [Males; %] HbA1c [%] HbA1c [mmol/mol] Platelet Count [10^9/L] Mean Platelet Volume [fL] Platelet Mass [fL/nL]
Type 1 Diabetes (N=691) 42.5 (12.4) 352; 51% 7.8 (1.4) 61 (16) 249 (65) 10.0 (1.7) 2448 (601)
AC C
EP
TE D
M AN U
SC
Data are reported as mean (standard deviation). P-values for comparison among the three groups.
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
Figure 1
Comparison, adjustment
Platelet Count
TE D
Type 1 diabetes vs Controls Unadjusted Age Age, Sex
Mean Platelet Volume
EP
Type 2 diabetes vs Controls Unadjusted Age Age, Sex
AC C
Type 2 vs Type 1 diabetes Unadjusted Age Age, Sex Age, Sex, HbA1c
0
10
20
30
10^9/L
40
18.2 (10.3, 26.2) 18.3 (10.3, 26.3) 12.2 (4.3, 20.2)
-0.3 (-0.5, -0.1) -0.3 (-0.5, -0.1) -0.3 (-0.5, -0.1)
34.5 (25.4, 43.5) 35.6 (25.7, 45.5) 30.9 (21.2, 40.7)
-0.6 (-0.8, -0.4) -0.6 (-0.9, -0.4) -0.6 (-0.9, -0.4)
16.2 17.3 18.7 19.5
50
(6.7, (6.9, (8.6, (9.8,
-0.3 -0.3 -0.3 -0.3
25.8) 27.6) 28.8) 29.3)
-1.0
-0.5 Femtoliter (fL)
0
(-0.5, (-0.6, (-0.6, (-0.6,
-0.1) -0.1) -0.1) -0.1)
-100
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
TE D
Figure 2
15 14
Type 1 diabetes
EP
Healthy control
12
AC C
Mean Platelet Volume (fL)
13
Type 2 diabetes
11 10 9 8 7 6
Healthy controls
Type 1 diabetes
Type 2
5 0
50
100
150
200
250
300
350
400
450
Platelet count (10^9/L)
500
550
600
650
700
75
ACCEPTED MANUSCRIPT
Figure 3
280
SC
260
p<0.001
220 2
2.2
2.4
1.8
2
p=0.101
2.2
2.4
TE D
10.5
M AN U
240
10.0
9.5
p=0.441
9.0 1.8
2
2.2
2.4
p=0.769
1.8
2
2.2
2.4
AC C
Mean Platelet Volume (fL)
RI PT
300
1.8
Platelet Mass (fL/nL)
Type 2 diabetes
EP
Platelet Count (x10^9)
Type 1 diabetes
2800 2600 2400
p<0.001
2200
p=0.086
1.8
2
2.2
2.4
1.8
2
2.2
2.4
(6.2)
(7.2)
(9.0)
(10.7)
(6.2)
(7.2)
(9.0)
(10.7)
Loge HbA1c (%)
ACCEPTED MANUSCRIPT
HIGHLIGHTS
Platelet indices have been investigated mainly in type 2 diabetes (T2DM)
•
Most of these studies have not accounted for potential confounders
•
We have found higher platelet mass in T2DM vs T1DM and healthy controls, accounting for age, sex, and Hb1Ac
•
The platelet volume-count relationship was different in T2DM vs T1DM
•
HbA1c was related to platelet mass and the volume-count relationship only in T1DM
AC C
EP
TE D
M AN U
SC
RI PT
•
S0939-4753(17)30137-0
DOI:
10.1016/j.numecd.2017.06.016
Reference:
NUMECD 1747
To appear in:
Nutrition, Metabolism and Cardiovascular Diseases
Received Date: 22 February 2017 Revised Date:
23 May 2017
Accepted Date: 27 June 2017
Please cite this article as: Zaccardi F, Rocca B, Rizzi A, Ciminello A, Teofili L, Ghirlanda G, De Stefano V, Pitocco D, Platelet indices and glucose control in type 1 and type 2 diabetes mellitus: a case–control study, Nutrition, Metabolism and Cardiovascular Diseases (2017), doi: 10.1016/j.numecd.2017.06.016. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Platelet indices and glucose control in type 1 and type 2 diabetes mellitus: a case–control study Zaccardi F 1,2
RI PT
Rocca B 3 Rizzi A 2 Ciminello A 4 Teofili L 4
SC
Ghirlanda G 2 De Stefano V 4
M AN U
Pitocco D 2
1
Diabetes Research Centre, University of Leicester, Leicester, UK Diabetes Care Unit, Catholic University School of Medicine, Rome, Italy 3 Institute of Pharmacology, Catholic University School of Medicine, Rome, Italy 4 Institute of Haematology, Catholic University School of Medicine, Rome, Italy
Corresponding Author
TE D
2
AC C
EP
Francesco Zaccardi Leicester Diabetes Centre, Leicester General Hospital Leicester, LE5 4PW, England Phone: 0116 258 4389 Email: [email protected]
Word Count: Abstract 272; Main Text 3513 Figures: 3 Tables: 1 Supplementary Material: 6 Tables, 2 Figures
Keywords: platelet count; platelet volume; platelet turnover; type 1 diabetes; type 2 diabetes; case-control Abbreviations: CGM: continuous glucose monitoring; MPV: Mean platelet volume; PLT: Platelet count; PM: Platelet mass; T1DM: Type 1 diabetes mellitus; T2DM: Type 2 diabetes mellitus; TX: Thromboxane
1
ACCEPTED MANUSCRIPT ABSTRACT Background and Aims: The relationship between platelet indices and glucose control may differ in type 1 (T1DM) and type 2 (T2DM) diabetes. We aimed to investigate differences in the mean platelet volume (MPV), platelet count, and platelet mass among patients with
RI PT
T1DM, T2DM, and healthy controls and to explore associations between these platelet indices and glucose control.
Methods and Results: 691 T1DM and 459 T2DM patients and 943 control subjects (blood
SC
donors) were included. HbA1c was measured in all subjects with diabetes and 36 T1DM patients further underwent 24h-continuous glucose monitoring to estimate short-term glucose
M AN U
control (glucose mean and standard deviation). Adjusting for age and sex, platelet count was higher and MPV lower in both T1DM and T2DM patients vs control subjects, while platelet mass (MPV x platelet count) resulted higher only in T2DM. Upon further adjustment for HbA1c, differences in platelet count and mass were respectively 19.5x10^9/L (95%CI: 9.8-
TE D
29.3; p<0.001) and 101fL/nL (12-191; p=0.027) comparing T2DM vs T1DM patients. MPV and platelet count were significantly and differently related in T2DM patients vs both T1DM and control subjects; this difference was maintained also accounting for HbA1c, age, and sex.
EP
Platelet mass and the volume-count relationship were significantly related to HbA1c only in
AC C
T1DM patients. No associations were found between platelet indices and short-term glucose control.
Conclusion: By accounting for confounders and glucose control, our data evidenced higher platelet mass and different volume-count kinetics in subjects with T2DM vs T1DM. Longterm glucose control seemed to influence platelet mass and the volume-count relationship only in T1DM subjects. These findings suggest different mechanisms behind platelet formation in T1DM and T2DM patients with long-term glycaemic control being more relevant in T1DM than T2DM.
2
ACCEPTED MANUSCRIPT INTRODUCTION Diabetes mellitus is a metabolic disorder associated with a 2-fold increase of microand macro-vascular atherothrombotic complications as compared to subjects without diabetes [1, 2]. Platelet activation is known to contribute to atherothrombosis development and acute
RI PT
major arterial events [3]. Consistently, an increased urinary thromboxane (TX)A2 excretion, a biomarker of in vivo platelet activation, was documented in type 2 diabetes mellitus (T2DM) patients with macrovascular complications already two decades ago [4]. Since then, many
SC
different platelet functional and/or morphological abnormalities have been reported in vivo, ex vivo, or in vitro in T2DM, altogether consistent with increased platelet activity and/or
M AN U
reduced antiplatelet drug responsiveness phenotypes [5]. Conversely, data on platelets in type 1 (T1)DM, are more limited. Recently, we have reported in young T1DM patients an increased TXA2 generation in vivo associated with microvascular damage [6]. Among different platelet morphological indices, a high mean volume (MPV) of
TE D
peripheral platelets is considered a marker associated with increased platelet activity in vivo, mainly related to the larger volume of newly-released platelets which display an increased pro-thrombotic activity [7]. High MPV has been associated with incident coronary heart
EP
disease events in T2DM [8] and in the general population [9]. Moreover, MPV has been
AC C
reported to independently predict a reduced pharmacological response to low dose aspirin in T2DM [10]. Consistently, a higher immature platelet fraction has been reported in T2DM patients with cardiovascular complications [11] and has been associated with macrovascular events in patients without diabetes [12]. Moreover, higher levels of immature platelets and have been associated with a reduced response to antiplatelet drugs in patients without [13, 14] and with T2DM [10]. Based on the above observations, the MPV has been often proposed as biomarker of poor outcomes and/or antiplatelet drug responsiveness in T2DM. However, not all the studies
3
ACCEPTED MANUSCRIPT have been consistent in reporting an increased MPV in T2DM vs non-T2DM subjects [1519]. In addition, platelet morphometric indices other than MPV, such as platelet count (PLT) and/or platelet distribution width have been investigated in T2DM and non-T2DM subjects, with inconsistent findings [15]. Data on platelet indices on T1DM are far more limited [20-
RI PT
22].
Under steady-state conditions of physiological magakariopoiesis, the platelet size is inversely related to the platelet count, and these parameters are inversely regulated to keep
SC
the platelet mass (PM = PLT x MPV) constant [23]. Therefore, the measure of only one morphometric platelet index might be poorly informative of the kinetics of platelet generation
M AN U
in vivo and be potentially misleading or give inconsistent findings. Furthermore, previous studies on T2DM and a single platelet morphometric index often lacked of adjustment for potential confounders known to affect MPV, PLT and PM, independently of diabetes [24], such as age, gender and ethnicity [25]. Moreover, whether and how glycaemic control can
TE D
affect the kinetics of platelet production in vivo is also unclear. Recently, high fasting glucose levels have been associated with high MPV in a large male population [24]; however, one fasting glucose measurement is poorly informative of the short- and long-term regulation of
EP
glucose metabolism or of the type of underlying metabolic defect (T1DM, T2DM, glucose
AC C
intolerance) [26]. Finally, investigating T1DM separately from T2DM is potentially relevant, since hyperglycaemia in T1DM generally does not cluster with other metabolic alterations or comorbidities as in T2DM. To help clarify these aspects, we performed a large, retrospective, case-control study
including T1DM, T2DM and healthy subjects and we investigated MPV, PLT, PM and their relationships in physiological and different diabetes conditions. We also investigated the effect of long- and short-term glucose control on the same platelet indices.
4
ACCEPTED MANUSCRIPT METHODS Population The present study is a retrospective analysis of the database from T1DM and T2DM
RI PT
subjects of the outpatient diabetes clinic of the “A. Gemelli” Hospital, Catholic University School of Medicine, Rome. For subjects with T1DM and T2DM, data collected during one calendar year (2013) were anonymously extracted from hospital datasets providing that there were information on age and sex, and HbA1c, MPV and PLT values from samples collected
SC
on the same day. In our outpatient Unit, T1DM is diagnosed as the presence of at least one of
M AN U
the diabetes-related autoantibodies (IA-2 protein tyrosine phosphatase, glutamic acid decarboxylase, or insulin antibody) in subjects needing insulin treatment and T2DM is diagnosed according to the American Diabetes Association criteria [27]. Patients with endstage renal failure and on dialysis were excluded. For the control group, we used an anonymised database including all blood donor volunteers during the same period (year
TE D
2013) and we extracted data with available information on age, gender, MPV and PLT. For the short-term glucose control study, a group of 36 uncomplicated (absence of
EP
macro- and micro-vascular disease and neuropathy) T1DM consenting patients were consecutively enrolled to undergo a 24-hour continuous glucose monitoring (CGM)
AC C
(CGMS® Guardian REAL-Time, Medtronic MiniMed, Northridge, CA, USA). The glucose sensor was inserted subcutaneously in the abdominal wall and patients were instructed to perform the required sensor calibration procedure according to manufacturer's instructions; at the end of CGM, fasting blood samples were taken to measure haemocromocitometric and biochemical variables. Resting systolic blood pressure was measured with a random-zero sphygmomanometer by a trained nurse; body mass index was computed as the ratio of weight in kilograms to the square of height in meters; waist circumference was calculated as the average of 2 measurements taken after inspiration and expiration at the midpoint between the 5
ACCEPTED MANUSCRIPT lowest rib and iliac crest; and waist-hip ratio was defined as waist girth/hip circumference measured at the trochanter major. The short-term glucose control study was approved by the
Hematological and Biochemical measurements
RI PT
institutional ethics committee and subjects signed an informed consent.
PLT and MPV were measured in K3-EDTA anticoagulated blood by an automatic blood cell cytometer (Sysmex SF-3000, Dasit, Milano, Italy). Blood samples were processed
SC
within 2 hrs after collection, according to the standard operating procedure of our Institution. In the group of patient with CGM-data, immature platelet fraction were counted by the
M AN U
Sysmex® XE-500 Instrument (Sysmex Corporation, Kobe, Japan).
HbA1c, blood glucose, and lipids were measured at the Department of Clinical Biochemistry: plasma glucose and whole blood HbA1c were measured using the hexokinase method and ion exchange high performance liquid chromatography, respectively; serum
TE D
triglyceride, high density lipoprotein cholesterol and low density lipoprotein cholesterol were measured using an Olympus auto-analyser (Olympus Corporation, Tokyo, Japan).
EP
Statistical Analysis
AC C
Given the availability of a large number of controls (blood donors) in the Institutional database, when estimating sample size the number of patients with T1DM and T2DM was considered the limiting factor. We therefore calculated the minimum number of T1DM and T2DM patients with 1:1 ratio between diabetes-specific cases and blood donors, a power of 0.9 and two-sided α=0.017 to account for multiple comparisons (T1DM vs controls; T2DM vs controls; T2DM vs T1DM). Assuming a mean MPV of 8.5 fL in controls and a common standard deviation (SD) for the three groups of 1.7 fL [15], with 400 participants per group we could detect pairwise differences of at least 0.44 fL. Similarly, assuming a mean PLT of
6
ACCEPTED MANUSCRIPT 241x103/µL in controls and a common SD of 71x103/µL [15], the same sample size allowed detecting pairwise differences of at least 18x103/µL. As no data have been reported on the relationship between platelet indices and short-term glucose control, it was not possible to perform formal sample size calculations for the short-term glucose control study.
RI PT
For all analyses, the natural logarithm-transformed of the non-normal distributed variable HbA1c was used. Descriptive data are presented as means and SD for continuous variables and number and percentages for categorical ones. Unadjusted correlation
SC
coefficients were calculated to assess the correlation between platelet indices and other continuous variables, whereas mean differences between groups were estimated for
M AN U
categorical factors. PM was calculated as MPV x PLT and expressed in fL/nL. Associations between platelet indices and other variables involved multiple linear regressions, progressively adjusted for age, sex, and HbA1c. Differences (∆) were estimated among the three groups using Bonferroni-corrected standard errors to account for multiple
TE D
comparisons. As none of the transformation allowed CGM-derived variables to be approximately normally distributed, associations with such variables were estimated using nonparametric tests. Differences in the relationship between MPV and PLT across the
EP
three groups were computed as the ratio of the difference between the coefficients
AC C
(slopes) of two groups and the coefficient of the reference group; pairwise estimations were adjusted for multiple testing and reported as percentages. All analyses were performed with Stata 14.1 (Stata Corp, College Station, TX, USA)
and results are reported with 95% confidence intervals (CIs). P-values <0.05 were considered statistically significant.
7
ACCEPTED MANUSCRIPT RESULTS Platelet indexes A total of 2,903 participants were included in the study: 691 T1DM, 459 T2DM, and
RI PT
943 control subjects; their characteristics and platelet indices are reported in Table 1. Overall, T2DM patients were slightly older than the other two groups, less females were present in the T1DM group, while the glycaemic control, as expressed by HbA1c, was similar in T1DM and T2DM groups. Unadjusted analyses showed that T2DM patients had the highest PLT and
SC
PM values among the three groups. Moreover, the analysis of the correlations between
M AN U
clinical/metabolic and platelet indexes showed that female subjects had consistently and significantly increased values of both PLT and PM in each group (p<0.001) (Supplementary Material, Table S1) while MPV was unrelated to sex. There was no association of age with any platelet index (Table S1).
After adjusting for age and sex, PLT and PM were still significantly higher in T2DM
TE D
vs. e control or T1DM groups (Figure 1). MPV resulted significantly although slightly lower in both T1DM (∆MPV -0.3 fL; 95% CI: -0.5, -0.1; p<0.001) and T2DM (-0.6 fL; -0.9, -0.4;
EP
p<0.001) vs control subjects and in T2DM vs T1DM subjects (-0.3 fL; -0.6, -0.1; p=0.007). The observation that T2DM patients had the highest PM, in spite of a slight reduction
AC C
in MPV, prompted us to investigate the relationship between MPV and PLT within each group, as expressed by the slope of the linear fitting of the values of the two indexes. As expected, there was an inverse relationship between MPV and PLT, although the type of dependency between these two variables differed among the three groups (Figure 2). In fact, the absolute value of the slope in T2DM subjects was 36% lower than in controls (95% CI: 14.4, 57.6; p<0.001) and 30.7% (7.2, 54.2; p=0.002) lower than in T1DM subjects (Table S2), At variance with T2DM, T1DM and control subjects showed superimposable slope
8
ACCEPTED MANUSCRIPT values (7.7%; -19.4, 34.7; p=0.5). The above results were consistent in the adjusted analyses as well (Table S2). These data overall indicate a smaller reduction of MPV as a function of increasing
RI PT
PLT values in T2DM as compared to the other two groups.
Long-term glucose control
Differences in platelet indexes were then analysed by adjusting for HbA1c in addition
SC
to age and sex, only in subjects with diabetes. After adjusting for HbA1c, PLT and PM remained higher in T2DM vs. T1DM, while MPV remained lower: ∆PLT, ∆PM and ∆MPV
M AN U
were respectively 19.5 x 10^9/L (95% CI: 9.8, 29.3; p<0.001), 101 fL/nL (12, 191; p=0.027) and -0.3 fL (-0.6, -0.1; p=0.003) (Figure 1). Moreover, after adjusting for HbA1c also the absolute value of the slope of the inverse relationship between MPV and PLT remained 33.4% (95% CI: 8.7, 58.1; p=0.001) significantly lower in T2DM than T1DM subjects (Table
TE D
S2).
HbA1c positively correlated with PLT and PM in T1DM, while it correlated only with PM in T2DM (Table S1). Given this association, we then investigated the distribution of age
EP
and sex-adjusted platelet indices according to quartiles of HbA1c. In the T1DM group there
AC C
was a progressive, concentration-depend increase of PLT and PM from the lowest to the highest HbA1c quartile (Figure 3). At variance with T1DM, T2DM showed non-significant trends for PM, MPV and PLT across the HbA1c quartiles (Figure 3). Given the influence of HbA1c on PM in T1DM, we then analysed the effect of
HbA1c on the relationship between MPV and PLT across the HbA1c quartiles. In T1DM, the absolute slope value was 41.1% (95% CI: 14.3, 67.8; p=0.003) significantly smaller in patients in the highest HbA1c quartile as compared to the lowest quartile (Figure S1 and Table S3). No differences in slopes were observed across the extreme HbA1c quartiles in
9
ACCEPTED MANUSCRIPT T2DM (37.6%; -10.5, 85.3; p=0.1), consistently with the lack of association with PM. Results were similar in adjusted analyses (Table S3).
Short-term glucose control
RI PT
Clinical, metabolic, and CGM-derived data in 36 uncomplicated T1DM subjects are reported in Table S4 and Figure S2. The median age and diabetes duration were 35 (interquartile range: 27-42) and 14 (8-24) years, respectively. CGM-median glucose was 123
SC
(interquartile range: 104-160) mg/dl, glucose coefficient of variation 28% (22-40) and HbA1c 7.0% (6.5-7.8).
M AN U
Table S5 shows correlation coefficients between platelet indices and CGM-derived glucose variables. No association was found for each platelet index with GM, GSD, or coefficient of variation of 24-hour glucose values. Given the small sample size, other clinical/metabolic characteristics and correlations are reported as explorative data in Table S4
AC C
EP
TE D
and Table S6, respectively.
10
ACCEPTED MANUSCRIPT DISCUSSION To our knowledge, this is the first study which considered together different platelet indexes and their relationships, in large cohorts of T1DM, T2DM and healthy
RI PT
subjects. Data on age and sex allowed the estimation of differences accounting for these important confounders; moreover, HbA1c and 24-hour glucose data, along with an accurate diabetes phenotyping, helped elucidating the role of short and long term glucose control and differentiate its impact on platelet generation in T1DM and T2DM.
SC
In fact, most of previous studies investigating differences in platelet
M AN U
morphometric indexes in diabetes usually considered a single parameter with few exceptions [16, 28, 29] and did not study the relationship between PLT and MPV, which is an indirect index of megakariopoiesis in vivo. Moreover, potential confounders were not considered, virtually only T2DM subjects were included, or control groups were heterogeneous (i.e., general population, non-T2DM patients with chronic cardiovascular
TE D
disease or acute medical conditions) [15]. These limitations have so far blurred the possibility to clarify the presence and extent of the possible differences in platelet
EP
indexes in T1DM and T2DM, their relationships, and the relative importance of glucose control both at short- and long-term. Our study attempted to overcome these limitations.
AC C
We investigated MPV and PLT, their product (PM), and their relationship, because one or even two parameters without studying their relationship scarcely reflect the kinetics of in vivo platelet generation. Complex feedback mechanisms converging to the bone marrow megakaryocytes operate to maintain constant the PM under normal conditions [30], with an inverse relationship between platelet volume and count [31]. In some clinical settings, the platelet mass has been demonstrated to be a reliable index of thrombopoiesis [32, 33]. Abnormal megakaryopoietic mechanisms and increased platelet turnover have been often hypothesized for T2DM [34]. However, studies on primary 11
ACCEPTED MANUSCRIPT megakaryocytes in vivo are hardly feasible in patients with non-haematological diseases, such as diabetes. Thus the study of the PM and the relationship of MPV and PLT might be particularly helpful in this context. Our findings indicated that T2DM is characterized by a significant increase of
RI PT
PM, largely driven by a changed inverse relationship between PLT and MPV, whereby the increase in PLT was associated with a reduced proportional decrease in MPV. This feature characterised T2DM only as it was not observed in T1DM which showed a PLT-
SC
MPV relationship similar to healthy subjects. Overall these data indicate different kinetic mechanism(s) regulating platelet production in T2DM vs both normal subjects and
M AN U
T1DM. Of note, this characteristic remained after adjusting for potential confounders such as age, sex and, more importantly, HbA1c. Furthermore, in T2DM this different relationship between MPV and PLT appeared not influenced by HbA1c levels. These observations may suggest that extra-glycaemic factors are possibly prevalent in
TE D
modulating platelet generation in T2DM. In addition, our data are consistent with studies in T2DM animal models indicating platelet hyper-regeneration and increased thrombotic risk, independently of blood glucose levels [35]. Our results are consistent with and
EP
enlarge a previous study, showing an increased megakaryocyte ploidy in the bone
AC C
marrow of subjects with diabetes [34], being nuclear ploidy a morphological marker of active platelet production. Moreover, a higher fraction of immature platelets in T2DM [11] has been associated with a reduced response to aspirin which was corrected by a more daily frequent dosing (every 12 hours) rather than by doubling the daily aspirin dose [10, 36-38] which would be consistent with a faster 24-hour platelet turnover. At variance with T2DM, platelet production mechanisms appear overall unchanged in T1DM. In spite of a higher PLT and lower MPV, nevertheless the inverse relationship between the two parameters was fully superimposable to healthy subjects,
12
ACCEPTED MANUSCRIPT with similar total PM. These results are in line with previous evidence showing normal immature platelet counts and preserved response to once-daily antiplatelet therapy in T1DM vs matched controls [6]. At variance with T2DM, T1DM patients showed a stronger and concentration-dependent, direct association between PM or MPV-PLT
RI PT
relationship with HbA1c. Moreover, the subgroup of T1DM with the worse long-term glycaemic control (mean HbA1c 9.5%) showed a significant alteration of the MPV-PLT relationship. Interestingly, in this subgroup the increase in PM appeared mainly driven by
SC
a disproportionate increase in platelet count not associated with a proportional reduction of the MPV which seemed stable across the HbA1c quartiles. An ‘osmotic’ effect of
M AN U
higher plasma glucose on platelet volume in this subgroup cannot be excluded [39]. However, we cannot also exclude that higher values of HbA1c in T1DM could impair platelet turnover to an extent similar to T2DM, acting on the central platelet production rather than on peripheral characteristics.
TE D
The differences in platelet indices and turnover possibly reflect the different pathophysiological mechanisms operating in T1DM vs T2DM [40]. In T2DM, the hyperglycaemia is more likely clustered with metabolic abnormalities related to insulin (i.e.,
hypertension,
EP
resistance
dyslipidaemia,
abdominal
obesity,
low-grade
AC C
inflammation). These abnormalities have been associated with both higher platelet activation [41, 42] and larger platelet volume [43, 44]. In particular, inflammatory mediators such as interleukin-1, interleukin-6, tumour necrosis factor alpha, or interferon gamma, are known to enhance thrombopoiesis with a shift towards the synthesis of younger, larger and prothrombotic platelets [45]. Platelet generation in T1DM and T2DM require further investigation. In the last few years short-term, rapid glucose excursions (“glycaemic variability”) have been proposed as an HbA1c-independent risk factor for vascular
13
ACCEPTED MANUSCRIPT complications [26] and associated with platelet activation [46]. To further investigate the role of glucose control independent of other potential confounders, in T1DM subjects without complications where hyperglycaemia is the only risk factor, we obtained detailed information on glucose excursions from CGM-data and platelet indices. Our result did
RI PT
not show any association between short-term glucose control parameters and platelet indices.
We should acknowledge some limitations of this study. It has been reported that
SC
MPV progressively increases when blood is collected in EDTA until 2 hours, which has been suggested as the optimal measuring time after venepuncture [47, 48]. In our study
M AN U
the time interval between collection and analysis was not recorded, but, being a singlecentre study with standardized procedures, it can be reasonably expected that the distribution of the interval between blood drawing and analysis did not differ between the study groups. Moreover, the maximum swelling of platelets in EDTA occur in the first 5
TE D
minutes, with a residual MPV increase by only 10-15% over the next 2 hours [47]. While we adjusted the analyses for well-established confounders [25, 49], other variables which could potentially influence the association between diabetes and platelet
EP
indexes (such as cardiovascular disease risk factors or treatments, micro- and
AC C
macro-vascular complications, body mass index, or glomerular filtration) were not available for the overall population. Although a clear evidence on the role of these factors as confounders or effect-modifiers is lacking [15, 24], future studies are required to evaluate whether and how such parameters contribute to the differences in platelet indexes in subjects with and without diabetes. Lastly, we did not assess the association between short-term glucose control and platelet indices in T2DM. On the other hand, strengths of our study included the accurate definition of diabetes cases which allowed a clear distinction between T1DM and T2DM, the large sample size
14
ACCEPTED MANUSCRIPT (particularly T1DM subjects), and the inclusion of controls who, by definition, had no haematological disorders which could influence megakaryopoiesis.
Conclusions and future area of research
RI PT
In this study, we included a large sample of well-defined T1DM, T2DM and healthy subjects and, accounting for suggested potential confounders [49], we investigated multiple platelet parameters and their relationship to unravel the separate
SC
role of glucose and diabetes type on platelet indexes and generation. We observed that the physiological feedback mechanisms to maintain PM were preserved in T1DM except
M AN U
for patients with poor long-term glucose control. Conversely, T2DM had consistently high PLT, PM and a different inverse relationship between the MPV and PLT, poorly influenced by glycaemic control.
Given the considerable paucity of data in T1DM and on the role of short-term
TE D
glucose control, further studies are warranted to confirm and enlarge our results. Moreover, future studies in subjects with diabetes might quantify the potential ability of platelet indices and their relationships to determine whether these indices could be
AC C
EP
potential target or indicator of the beneficial effect of therapeutic approaches [50].
15
ACCEPTED MANUSCRIPT ACKNOWLEDGMENTS AUTHOR CONTRIBUTION FZ, DP, BR study idea and design; FZ, AR, AC, LT, VDS data extraction; FZ data analysis; FZ, BR first manuscript draft. All authors provided study critical revision, draft amendments, and approved the final version to publish. FZ is the study guarantor.
RI PT
CONFLICT OF INTEREST None related to this paper for all Authors.
AC C
EP
TE D
M AN U
SC
FUNDING The study was supported by grants from: Linea D3.2 2013-70201169 to BR; and Italian Ministry for University and Research ‘Fondo per il Sostegno dei Giovani’ Anno finanziario 2012 to AR.
16
ACCEPTED MANUSCRIPT REFERENCES
AC C
EP
TE D
M AN U
SC
RI PT
[1] Emerging Risk Factors C, Seshasai SR, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. The New England journal of medicine. 2011;364:829-41. [2] Livingstone SJ, Looker HC, Hothersall EJ, Wild SH, Lindsay RS, Chalmers J, et al. Risk of cardiovascular disease and total mortality in adults with type 1 diabetes: Scottish registry linkage study. PLoS medicine. 2012;9:e1001321. [3] Davi G, Patrono C. Platelet activation and atherothrombosis. The New England journal of medicine. 2007;357:2482-94. [4] Davi G, Catalano I, Averna M, Notarbartolo A, Strano A, Ciabattoni G, et al. Thromboxane biosynthesis and platelet function in type II diabetes mellitus. The New England journal of medicine. 1990;322:1769-74. [5] Kumbhani DJ, Marso SP, Alvarez CA, McGuire DK. State-of-the-Art: Hypo-responsiveness to oral antiplatelet therapy in patients with type 2 diabetes mellitus. Current cardiovascular risk reports. 2015;9:4. [6] Zaccardi F, Rizzi A, Petrucci G, Ciaffardini F, Tanese L, Pagliaccia F, et al. In Vivo Platelet Activation and Aspirin Responsiveness in Type 1 Diabetes. Diabetes. 2016;65:503-9. [7] Martin JF, Kristensen SD, Mathur A, Grove EL, Choudry FA. The causal role of megakaryocyteplatelet hyperactivity in acute coronary syndromes. Nature reviews Cardiology. 2012;9:658-70. [8] Han JY, Choi DH, Choi SW, Kim BB, Ki YJ, Chung JW, et al. Stroke or coronary artery disease prediction from mean platelet volume in patients with type 2 diabetes mellitus. Platelets. 2013;24:401-6. [9] Klovaite J, Benn M, Yazdanyar S, Nordestgaard BG. High platelet volume and increased risk of myocardial infarction: 39,531 participants from the general population. Journal of thrombosis and haemostasis : JTH. 2011;9:49-56. [10] Rocca B, Santilli F, Pitocco D, Mucci L, Petrucci G, Vitacolonna E, et al. The recovery of platelet cyclooxygenase activity explains interindividual variability in responsiveness to low-dose aspirin in patients with and without diabetes. Journal of thrombosis and haemostasis : JTH. 2012;10:1220-30. [11] Lee EY, Kim SJ, Song YJ, Choi SJ, Song J. Immature platelet fraction in diabetes mellitus and metabolic syndrome. Thrombosis research. 2013;132:692-5. [12] Ibrahim H, Schutt RC, Hannawi B, DeLao T, Barker CM, Kleiman NS. Association of immature platelets with adverse cardiovascular outcomes. Journal of the American College of Cardiology. 2014;64:2122-9. [13] Guthikonda S, Alviar CL, Vaduganathan M, Arikan M, Tellez A, DeLao T, et al. Role of reticulated platelets and platelet size heterogeneity on platelet activity after dual antiplatelet therapy with aspirin and clopidogrel in patients with stable coronary artery disease. Journal of the American College of Cardiology. 2008;52:743-9. [14] Stratz C, Bomicke T, Younas I, Kittel A, Amann M, Valina CM, et al. Comparison of Immature Platelet Count to Established Predictors of Platelet Reactivity During Thienopyridine Therapy. Journal of the American College of Cardiology. 2016;68:286-93. [15] Zaccardi F, Rocca B, Pitocco D, Tanese L, Rizzi A, Ghirlanda G. Platelet mean volume, distribution width, and count in type 2 diabetes, impaired fasting glucose, and metabolic syndrome: a metaanalysis. Diabetes/metabolism research and reviews. 2015;31:402-10. [16] Kim JH, Kang SB, Kang JI, Kim JW, Kim SY, Bae HY. The relationship between mean platelet volume and fasting plasma glucose differs with glucose tolerance status in a Korean general population: gender differences. Platelets. 2013;24:469-73. [17] Hendra TJ, Oswald GA, Yudkin JS. Increased mean platelet volume after acute myocardial infarction relates to diabetes and to cardiac failure. Diabetes research and clinical practice. 1988;5:63-9.
17
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
[18] Abali G, Akpinar O, Soylemez N. Correlation of the coronary severity scores and mean platelet volume in diabetes mellitus. Advances in therapy. 2014;31:140-8. [19] Bavbek N, Kargili A, Kaftan O, Karakurt F, Kosar A, Akcay A. Elevated concentrations of soluble adhesion molecules and large platelets in diabetic patients: are they markers of vascular disease and diabetic nephropathy? Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. 2007;13:391-7. [20] Sterner G, Carlson J, Ekberg G. Raised platelet levels in diabetes mellitus complicated with nephropathy. Journal of internal medicine. 1998;244:437-41. [21] van der Planken MG, Vertessen FJ, Vertommen J, Engelen W, Berneman ZN, De Leeuw I. Platelet prothrombinase activity, a final pathway platelet procoagulant activity, is overexpressed in type 1 diabetes: no relationship with mean platelet volume or background retinopathy. Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis. 2000;6:65-8. [22] Sharpe PC, Trinick T. Mean platelet volume in diabetes mellitus. The Quarterly journal of medicine. 1993;86:739-42. [23] Kuter DJ. Milestones in understanding platelet production: a historical overview. British journal of haematology. 2014;165:248-58. [24] Panova-Noeva M, Schulz A, Hermanns MI, Grossmann V, Pefani E, Spronk HM, et al. Sex-specific differences in genetic and nongenetic determinants of mean platelet volume: results from the Gutenberg Health Study. Blood. 2016;127:251-9. [25] Biino G, Santimone I, Minelli C, Sorice R, Frongia B, Traglia M, et al. Age- and sex-related variations in platelet count in Italy: a proposal of reference ranges based on 40987 subjects' data. PloS one. 2013;8:e54289. [26] Zaccardi F, Pitocco D, Ghirlanda G. Glycemic risk factors of diabetic vascular complications: the role of glycemic variability. Diabetes/metabolism research and reviews. 2009;25:199-207. [27] American Diabetes A. Diagnosis and classification of diabetes mellitus. Diabetes care. 2014;37 Suppl 1:S81-90. [28] Shah B, Sha D, Xie D, Mohler ER, 3rd, Berger JS. The relationship between diabetes, metabolic syndrome, and platelet activity as measured by mean platelet volume: the National Health And Nutrition Examination Survey, 1999-2004. Diabetes care. 2012;35:1074-8. [29] Verdoia M, Schaffer A, Barbieri L, Cassetti E, Nardin M, Bellomo G, et al. Diabetes, glucose control and mean platelet volume: a single-centre cohort study. Diabetes research and clinical practice. 2014;104:288-94. [30] Kaushansky K. Historical review: megakaryopoiesis and thrombopoiesis. Blood. 2008;111:981-6. [31] Bessman JD, Williams LJ, Gilmer PR, Jr. Mean platelet volume. The inverse relation of platelet size and count in normal subjects, and an artifact of other particles. American journal of clinical pathology. 1981;76:289-93. [32] Kim MJ, Park PW, Seo YH, Kim KH, Seo JY, Jeong JH, et al. Comparison of platelet parameters in thrombocytopenic patients associated with acute myeloid leukemia and primary immune thrombocytopenia. Blood coagulation & fibrinolysis : an international journal in haemostasis and thrombosis. 2014;25:221-5. [33] Gerday E, Baer VL, Lambert DK, Paul DA, Sola-Visner MC, Pysher TJ, et al. Testing platelet mass versus platelet count to guide platelet transfusions in the neonatal intensive care unit. Transfusion. 2009;49:2034-9. [34] Brown AS, Hong Y, de Belder A, Beacon H, Beeso J, Sherwood R, et al. Megakaryocyte ploidy and platelet changes in human diabetes and atherosclerosis. Arteriosclerosis, thrombosis, and vascular biology. 1997;17:802-7. [35] Hernandez Vera R, Vilahur G, Ferrer-Lorente R, Pena E, Badimon L. Platelets derived from the bone marrow of diabetic animals show dysregulated endoplasmic reticulum stress proteins that contribute to increased thrombosis. Arteriosclerosis, thrombosis, and vascular biology. 2012;32:2141-8. 18
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
SC
RI PT
[36] Bethel MA, Harrison P, Sourij H, Sun Y, Tucker L, Kennedy I, et al. Randomized controlled trial comparing impact on platelet reactivity of twice-daily with once-daily aspirin in people with Type 2 diabetes. Diabetic medicine : a journal of the British Diabetic Association. 2016;33:224-30. [37] Dillinger JG, Drissa A, Sideris G, Bal dit Sollier C, Voicu S, Manzo Silberman S, et al. Biological efficacy of twice daily aspirin in type 2 diabetic patients with coronary artery disease. American heart journal. 2012;164:600-6 e1. [38] Spectre G, Arnetz L, Ostenson CG, Brismar K, Li N, Hjemdahl P. Twice daily dosing of aspirin improves platelet inhibition in whole blood in patients with type 2 diabetes mellitus and micro- or macrovascular complications. Thrombosis and haemostasis. 2011;106:491-9. [39] Martyn CN, Matthews DM, Popp-Snijders C, Tucker J, Ewing DJ, Clarke BF. Effects of sorbinil treatment on erythrocytes and platelets of persons with diabetes. Diabetes care. 1986;9:36-9. [40] Zaccardi F, Webb DR, Yates T, Davies MJ. Pathophysiology of type 1 and type 2 diabetes mellitus: a 90-year perspective. Postgraduate medical journal. 2016;92:63-9. [41] Davi G, Guagnano MT, Ciabattoni G, Basili S, Falco A, Marinopiccoli M, et al. Platelet activation in obese women: role of inflammation and oxidant stress. Jama. 2002;288:2008-14. [42] Santilli F, Vazzana N, Liani R, Guagnano MT, Davi G. Platelet activation in obesity and metabolic syndrome. Obesity reviews : an official journal of the International Association for the Study of Obesity. 2012;13:27-42. [43] Coban E, Ozdogan M, Yazicioglu G, Akcit F. The mean platelet volume in patients with obesity. International journal of clinical practice. 2005;59:981-2. [44] Sansanayudh N, Muntham D, Yamwong S, Sritara P, Akrawichien T, Thakkinstian A. The association between mean platelet volume and cardiovascular risk factors. European journal of internal medicine. 2016;30:37-42. [45] Burstein SA, Peng J, Friese P, Wolf RF, Harrison P, Downs T, et al. Cytokine-induced alteration of platelet and hemostatic function. Stem cells. 1996;14 Suppl 1:154-62. [46] Santilli F, Formoso G, Sbraccia P, Averna M, Miccoli R, Di Fulvio P, et al. Postprandial hyperglycemia is a determinant of platelet activation in early type 2 diabetes mellitus. Journal of thrombosis and haemostasis : JTH. 2010;8:828-37. [47] Jackson SR, Carter JM. Platelet volume: laboratory measurement and clinical application. Blood reviews. 1993;7:104-13. [48] Lance MD, van Oerle R, Henskens YM, Marcus MA. Do we need time adjusted mean platelet volume measurements? Laboratory hematology : official publication of the International Society for Laboratory Hematology. 2010;16:28-31. [49] Harrison P, Goodall AH. Studies on Mean Platelet Volume (MPV) - New Editorial Policy. Platelets. 2016;27:605-6. [50] Asher E, Fefer P, Shechter M, Beigel R, Varon D, Shenkman B, et al. Increased mean platelet volume is associated with non-responsiveness to clopidogrel. Thrombosis and haemostasis. 2014;112:137-41.
19
ACCEPTED MANUSCRIPT Figure Legends Figure 1: Absolute differences in platelet count (x109/L), mean platelet volume (fL), and platelet mass (fL/nL).
RI PT
The figure depicts and reports differences (∆) with 95% confidence intervals comparing the first vs the second group, for each comparison (i.e., in age and sex adjusted analysis, platelet count was 18.7 x109/L greater and mean platelet volume 0.3 fL lower comparing Type 2 vs Type 1 diabetes patients).
Figure 2: Relationship between mean platelet volume and platelet count, by diabetes group.
M AN U
SC
The figure shows the linear fitting of mean platelet volume and platelet count. Slope and adjusted R2 were respectively: -0.0108 and 0.136 for Healthy controls; -0.0099 and 0.152 for Type 1 diabetes patients; and -0.0069 and 0.136 for Type 2 diabetes patients.
Figure 3: Relationship between platelet indices and HbA1c, by diabetes group.
AC C
EP
TE D
Platelet indices means (squares) and 95% confidence intervals (spikes) are calculated within diabetes-specific quartiles of HbA1c levels and plotted against mean HbA1c levels within each quartile. HbA1c values within brackets are geometric means and P-values indicate age and sex-adjusted p for linear trend. HbA1c [mmol/mol] = 10.9 * HbA1c [%] – 23.5.
20
Table 1: Characteristic of the subjectsACCEPTED included in the study MANUSCRIPT Controls (N=943) 41.8 (10.1) 675; 72% 231 (32) 10.3 (1.5) 2355 (513)
Variable
Type 2 Diabetes (N=459) 56.5 (17.5) 274; 60% 7.9 (2.2) 63 (24) 265 (90) 9.7 (1.7) 2522 (797)
P-value <0.001 <0.001 0.110 0.110 <0.001 <0.001 <0.001
RI PT
Age [years] Sex [Males; %] HbA1c [%] HbA1c [mmol/mol] Platelet Count [10^9/L] Mean Platelet Volume [fL] Platelet Mass [fL/nL]
Type 1 Diabetes (N=691) 42.5 (12.4) 352; 51% 7.8 (1.4) 61 (16) 249 (65) 10.0 (1.7) 2448 (601)
AC C
EP
TE D
M AN U
SC
Data are reported as mean (standard deviation). P-values for comparison among the three groups.
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
Figure 1
Comparison, adjustment
Platelet Count
TE D
Type 1 diabetes vs Controls Unadjusted Age Age, Sex
Mean Platelet Volume
EP
Type 2 diabetes vs Controls Unadjusted Age Age, Sex
AC C
Type 2 vs Type 1 diabetes Unadjusted Age Age, Sex Age, Sex, HbA1c
0
10
20
30
10^9/L
40
18.2 (10.3, 26.2) 18.3 (10.3, 26.3) 12.2 (4.3, 20.2)
-0.3 (-0.5, -0.1) -0.3 (-0.5, -0.1) -0.3 (-0.5, -0.1)
34.5 (25.4, 43.5) 35.6 (25.7, 45.5) 30.9 (21.2, 40.7)
-0.6 (-0.8, -0.4) -0.6 (-0.9, -0.4) -0.6 (-0.9, -0.4)
16.2 17.3 18.7 19.5
50
(6.7, (6.9, (8.6, (9.8,
-0.3 -0.3 -0.3 -0.3
25.8) 27.6) 28.8) 29.3)
-1.0
-0.5 Femtoliter (fL)
0
(-0.5, (-0.6, (-0.6, (-0.6,
-0.1) -0.1) -0.1) -0.1)
-100
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
TE D
Figure 2
15 14
Type 1 diabetes
EP
Healthy control
12
AC C
Mean Platelet Volume (fL)
13
Type 2 diabetes
11 10 9 8 7 6
Healthy controls
Type 1 diabetes
Type 2
5 0
50
100
150
200
250
300
350
400
450
Platelet count (10^9/L)
500
550
600
650
700
75
ACCEPTED MANUSCRIPT
Figure 3
280
SC
260
p<0.001
220 2
2.2
2.4
1.8
2
p=0.101
2.2
2.4
TE D
10.5
M AN U
240
10.0
9.5
p=0.441
9.0 1.8
2
2.2
2.4
p=0.769
1.8
2
2.2
2.4
AC C
Mean Platelet Volume (fL)
RI PT
300
1.8
Platelet Mass (fL/nL)
Type 2 diabetes
EP
Platelet Count (x10^9)
Type 1 diabetes
2800 2600 2400
p<0.001
2200
p=0.086
1.8
2
2.2
2.4
1.8
2
2.2
2.4
(6.2)
(7.2)
(9.0)
(10.7)
(6.2)
(7.2)
(9.0)
(10.7)
Loge HbA1c (%)
ACCEPTED MANUSCRIPT
HIGHLIGHTS
Platelet indices have been investigated mainly in type 2 diabetes (T2DM)
•
Most of these studies have not accounted for potential confounders
•
We have found higher platelet mass in T2DM vs T1DM and healthy controls, accounting for age, sex, and Hb1Ac
•
The platelet volume-count relationship was different in T2DM vs T1DM
•
HbA1c was related to platelet mass and the volume-count relationship only in T1DM
AC C
EP
TE D
M AN U
SC
RI PT
•