Endocrine DOI 10.1007/s12020-014-0451-3
ORIGINAL ARTICLE
Association between whole blood viscosity and arterial stiffness in patients with type 2 diabetes mellitus Ying Li • Xiu-xia Tian • Tiemin Liu Rui-tao Wang
•
Received: 16 May 2014 / Accepted: 9 October 2014 Ó Springer Science+Business Media New York 2014
Abstract Type 2 diabetes mellitus (DM) carries an increased risk for cardiovascular complications. The brachial-ankle pulse wave velocity (baPWV) is an index for early atherosclerotic changes. Recently, the effect of altered blood rheology on atherosclerosis has received attention. Therefore, this study aimed to examine the association of hemorheological parameters with baPWV in patients with DM. In this cross-sectional study, we investigated the relationship between rheological parameters and baPWV in 323 control subjects (160 men and 163 women) and 382 patients with DM (170 men and 212 women). The participants with DM had higher whole blood viscosity (WBV) levels both at low shear rate (3 s-1) and at high shear rate (200 s-1) than those without DM. Different metabolic parameters were compared across WBV (3 s-1) quartiles. The mean values of baPWV gradually increased with WBV (3 s-1) quartiles. In addition, there was a positive correlation between baPWV and WBV 3 s-1 in patients with DM after adjusting confounding factors (r = 0.285, p = 0.039). Stepwise multiple linear regression analysis further revealed that WBV (3 s-1) is a
Y. Li X. Tian R. Wang (&) Department of Geriatrics, The Second Affiliated Hospital, Harbin Medical University, NO. 246 Xuefu ST, Nangang District, Harbin 150086, Heilongjiang, China e-mail: [email protected] Y. Li International Physical Examination and Healthy Center, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang, China T. Liu Division of Hypothalamic Research, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX 75390, USA
significant determinant for increased baPWV in DM (b = 0.184; p \ 0.001). However, there were no association between WBV (3 s-1) and baPWV in control subjects. The findings showed that baPWV increased as WBV (3 s-1) elevated in DM. Moreover, WBV (3 s-1) is independently associated with baPWV even after adjusting other cardiovascular risk factors. Early detection of abnormal WBV levels at low shear rate should warrant for early search of undetected arterial stiffness in patients with DM. Keywords Type 2 diabetes mellitus Whole blood viscosity Brachial-ankle pulse wave velocity Arterial stiffness
Introduction Type 2 diabetes mellitus (DM) is associated with an increased risk of stroke and coronary heart disease (CHD) and non-vascular mortality [1, 2]. The occurrence of insulin resistance accompanied with hyperviscosity worsens the state of atherosclerosis in patients with DM. Furthermore, both DM and hyperviscosity have the tendency to develop thrombosis [3]. Recent studies demonstrated that hyperviscosity in DM is strongly influenced by the excellence of glycemic control [4–6]. Arterial stiffness due to decreased arterial compliance is one of the major signs of vascular aging [7]. Elevated arterial stiffness, an indicator of subclinical atherosclerosis, is associated with myocardial infarction, heart failure, stroke, renal disease, and all-cause mortality [8]. Brachialankle pulse wave velocity (baPWV) measurement, a simple, non-invasive, and automated measurement method, reflects the stiffness of muscular arteries and is widely used
123
Endocrine
as an index of arterial stiffness and vascular damage. Moreover, recent reports revealed that PWV is a forceful independent marker of cardiovascular disease and a powerful determinant of total mortality in diabetic patients [9, 10]. Altered hemorheological parameters play a key role in atherogenesis. Many cardiovascular risk factors, including aging, obesity, carotid intima-media thickness, are linked with changes of rheological parameters [11–13]. The risk of acute myocardial infarction and cardiovascular death increases with elevations in whole blood viscosity (WBV) [14, 15]. A recent study confirmed that WBV is a predictor of cardiovascular events [16]. In addition, marked hemorheological impairments were observed in diabetic patients and a high WBV is associated with increased insulin resistance [17–19]. Based on the assumption that both baPWV and hemorheological parameters are related to cardiovascular disease and both hemorheological parameters and vascular tone cooperate in regulating microvascular perfusion [20], we postulated that there would be a close relationship between the levels of baPWV and hemorheological parameters. Therefore, the aim of the study was to examine if rheological parameters are independently associated with baPWV in patients with DM.
Research design and methods Study population We studied 705 randomly selected subjects who visited International Physical Examination and Healthy Center, Harbin, China, from January 2009 through December 2010. This is a cross-sectional study and there are 382 patients with DM and 323 control subjects. Control subjects were matched for age, sex, body mass index (BMI), and smoking status. The participants generally underwent health status examination every 1 year. There were 375 (53.2 %) women and 330 (46.8 %) men in our study. The mean ages were 56.3 ± 5.9 and 56.8 ± 6.2 years, respectively. We obtained informed consent from all subjects. The study protocol was approved by the Ethics Committee of the Second Hospital of Harbin Medical University, China.
position using an automated sphygmomanometer, after a 15-min rest period. The mean systolic and diastolic blood pressure was calculated after two measurements. The BMI was calculated as the weight (kg) divided by the square of the height (m2).
Biochemical analyses Fasting venous blood samples were collected for the analysis. The values included total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL), lowdensity lipoprotein cholesterol (LDL), and fasting plasma glucose (FPG). All assays were conducted at the Laboratory of Analytical Biochemistry at the Second Hospital of Harbin Medical University, Harbin, using a biochemical analyzer (Modular Analytics, Roche, Mannheim, Germany). The HbA1c level was measured using high-performance liquid chromatography by HbA1c analyzer (VariantTM II; BioRad, Hercules, CA, USA). Hemoglobin was determined with an autoanalyzer (Sysmex XE-2100, Kobe, Japan). WBV was determined at shear rates between 3 and 200 s-1 corrected hematocrit of 45 % at 37 °C using a viscometer (Succeeder SA-9000, Beijing, China). For high shear rate, the intra- and inter-assay coefficient variations were 2.7 and 5.6 %, respectively. For low shear rate, the intra- and interassay coefficient variations were 4.6 and 9.8 %, respectively. Plasma viscosity was measured by Harkness method and hematocrit was evaluated by microcentrifugation. Plasma fibrinogen concentrations were assayed on the Beckman Coulter ACL-TOP analyzer (Instrumentation Laboratory, Lexingtion, MA, USA). All measurements were performed within 2 h of sampling. DM was defined as fasting serum glucose was C7.0 mmol/L or non-fasting serum glucose was C11.1 mmol/L or as taking prescription medications. For the subjects with impaired fasting glucose, DM was diagnosed if a 2-h postglucose level after a 75-g oral glucose tolerance test C11.1 mmol/L. Hypertension was defined as taking antihypertensive medication or having blood pressure 140/90 mmHg at the initial examinations. The Modification of Diet in Renal Disease (MDRD) equation was used to estimate glomerular filtration rate (eGFR). MDRD equation was eGFR = 186.3 9 (SCr)-1.154 9 (age)-0.203(9 0.742 if female) [21].
Clinical examination Exclusion criteria Clinical data, including medical history, smoking status, and medication use were recorded for each participant. All the subjects underwent physical examination which included anthropometric and blood pressure measurements. Blood pressure was measured in the right arm in the seated
123
Exclusion criteria include tumor, autoimmune diseases, rheumatoid arthritis, hematological disorders, chronic liver and kidney diseases, infection, cancer, CHD, atrial fibrillation, and stroke.
Endocrine Table 1 Characteristics of the analyzed participants according to DM status
Variables N
DM type 2 diabetes mellitus, BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, TC total cholesterol, TG triglyceride, HDL high-density lipoprotein cholesterol, LDL low-density lipoprotein cholesterol, FPG fasting plasma glucose, baPWV brachial-ankle pulse wave velocity, eGFR estimated glomerular filtration rate, WBV whole blood viscosity, PV plasma viscosity, ACEI angiotensin-converting enzyme inhibitor, ARB angiotensin II receptor antagonist, CCB calcium channel blocker p value was calculated by the student’s t test or Mann– Whitney U test or Chi-square test
382
Without DM
P value
323
Age (year)
56.8 (6.0)
56.2 (6.0)
Sex (male, %)
170 (44.5)
160 (49.5)
0.182
BMI (kg/m2)
25.4 (3.0)
25.1 (3.0)
0.147
Smoker (n, %)
101 (26.4)
Drinking (n, %) Data are shown as means (SD) or median (inter-quartile range) or percentage
With DM
SBP (mmHg)
78 (24.1)
0.149
0.486
97 (25.4)
85 (26.3)
0.780
135.7 (13.0)
132.1 (10.4)
\0.001
DBP (mmHg)
82.2 (6.7)
79.5 (7.8)
\0.001
TC (mmol/L)
5.62 (0.89)
4.85 (0.80)
\0.001
TG (mmol/L)
3.04 (2.47–3.65)
2.36 (1.94–2.83)
\0.001
HDL (mmol/L)
1.27 (1.11–1.44)
1.52 (1.33–1.71)
\0.001
LDL (mmol/L)
2.70 (0.72)
2.41 (0.70)
\0.001
FPG (mmol/L)
6.56 (6.14–6.96)
5.15 (4.85–5.51)
\0.001
Hemoglobin A1c (%)
7.51 (0.87)
4.80 (0.43)
\0.001
73.8 (16.2) 1571.1 (105.4)
75.4 (12.4) 1428.9 (102.5)
0.117 \0.001
125.0 (10.9)
123.9 (10.7)
47.4 (3.3)
47.1 (4.3)
Fibrinogen (mg/dl)
367.9 (63.7)
333.5 (69.8)
WBV 3 s-1 (mPa s)
eGFR (mL/min/1.73 m2) BaPWV (cm/s) Hemoglobin (g/dl) Hematocrit (%)
0.132 0.316 \0.001
10.15 (1.35)
8.56 (0.90)
\0.001
WBV 200 s-1 (mPa s)
6.50 (0.36)
5.61 (0.37)
\0.001
PV (mPa s)
1.60 (0.08)
1.53 (0.08)
\0.001
Hypertension n (%)
145 (38.0)
109 (33.7)
0.246
ACEIs/ARBs n (%)
73 (19.1)
67 (20.7)
0.588
CCBs n (%)
70 (18.3)
63 (19.5)
0.690
Statins n (%)
87 (22.8)
58 (17.9)
0.115
Aspirin n (%)
43 (11.3)
26 (8.0)
Measurement of BaPWV BaPWV was measured using an automatic device (model MB3000, M&B Electronic Instruments, Beijing, China). The subjects rested in the supine position for 5 min. The baPWV was automatically calculated according to the formula (L/PTT). L is the difference between the length from heart to ankle and the length from heart to brachium. PTT was the pulse transit time between the brachial and tibial arterial waveforms. Mean right and left baPWV value was calculated during analysis. All measurements were conducted by a single examiner who was blinded to the clinical data. The method was validated in a previous report [22, 23].
0.153
H was used for continuous variables among multiple groups. Correlations between baPWV and rheological parameters were tested by partial correlation. Stepwise multiple linear regression analysis was performed to assess the correlation between baPWV and WBV (3 s-1). The participants with DM were classified into quartiles by their WBV (3 s-1) levels. The WBV (3 s-1) quartiles were Q1 (B9.06 mPa s), Q2 (9.07–9.79 mPa s), Q3 (9.80–10.88 mPa s), and Q4 (C10.89 mPa s). Variables such as TG, HDL, and FPG were logarithmically transformed before statistical analysis to approximate a normal distribution. Values at p \ 0.05 were considered to be statistically significant. Statistical analyses were conducted using the SPSS software package version 17.0 (SPSS Inc., Chicago, IL, USA).
Statistical analysis Results All data were expressed as mean ± SD or median (IQR) or percentage. The Chi-square statistical test was used for categorical variables, while the student’s t test or Mann– Whitney U test was used for continuous variables between the two groups and one-way ANOVA or Kruskal–Wallis
The clinical and laboratory characteristics of all participants are shown in Table 1. The patients with DM had higher SBP, DBP, TG, TC, LDL, FPG, HbA1c, baPWV, WBV (3 s-1), WBV (200 s-1), plasma viscosity,
123
Endocrine Table 2 Clinical and biochemical characteristics of subjects with DM Quartiles of WBV (3 s-1) Q1 N
Q2 96
Age (years)
57.1 (6.0)
Sex (male, %)
46 (47.9)
2
BMI (kg/m )
25.0 (3.4)
Q3 98
Q4 93
56.7 (6.1)
56.6 (5.9)
48 (49.0)
95 56.9 (6.3)
35 (37.6)
25.5 (3.1)
25.5 (2.8)
P value
41 (43.2) 25.8 (2.6)
0.958 0.377 0.369
Smoker (n, %)
21 (21.9)
33 (33.7)
23 (24.7)
24 (25.3)
0.276
Drinking (n, %)
26 (27.1)
28 (28.6)
17 (18.3)
25 (26.3)
0.362
134.6 (14.0) 81.3 (6.9)
135.5 (13.0) 82.4 (6.3)
134.3 (11.6) 81.4 (6.6)
138.6 (13.0) 83.6 (6.9)
0.089 0.059
SBP (mmHg) DBP (mmHg) FPG (mmol/L)
6.53 (6.18–6.84)
6.41 (6.03–6.89)
6.63 (6.20–7.00)
6.67 (6.26–7.28)
0.015
TC (mmol/L)
5.52 (0.97)
5.58 (0.85)
5.62 (0.91)
5.75 (0.81)
0.323
TG (mmol/L)
2.83 (2.32–3.35)
3.03 (2.50–3.99)
3.15 (2.65–3.77)
3.12 (2.56–4.06)
0.021
HDL (mmol/L)
1.35 (1.20–1.49)
1.26 (1.09–1.46)
1.23 (1.07–1.38)
1.25 (1.10–1.43)
0.011
2.58 (0.79)
2.63 (0.71)
2.75 (0.63)
2.84 (0.73)
0.053
75.5 (16.1)
74.2 (16.5)
73.9 (15.7)
71.5 (16.3)
0.381
7.3 (0.8)
7.5 (1.0)
7.6 (0.8)
7.6 (0.8)
0.044
LDL (mmol/L) 2
eGFR (mL/min/1.73 m ) Hemoglobin A1c (%) DM duration (years) Hemoglobin (g/dl) Hematocrit (%)
2.3 (1.0)
2.3 (1.1)
2.5 (1.3)
2.5 (1.2)
0.617
123.3 (11.5)
125.0 (10.7)
125.0 (10.5)
126.8 (10.8)
0.184
47.2 (3.7)
47.3 (3.0)
47.4 (3.3)
47.7 (3.2)
0.795
357.0 (71.5)
363.6 (52.2)
365.5 (63.8)
385.6 (63.4)
0.013
WBV200 s (mPa s)
6.41 (0.35)
6.50 (0.35)
6.49 (0.36)
6.60 (0.36)
0.003
PV (mPa s)
1.59 (0.08)
1.60 (0.08)
1.60 (0.09)
1.61 (0.08)
0.875
Hypertension n (%) Statins n (%)
33 (34.4) 20 (20.8)
32 (32.7) 24 (24.5)
38 (40.9) 17 (18.3)
39 (41.1) 26 (27.4)
0.506 0.461
ACEIs/ARBs n (%)
16 (16.7)
16 (16.3)
17 (18.3)
21 (22.1)
0.718
CCBs n (%)
15 (15.6)
13 (13.3)
20 (21.5)
17 (17.9)
0.478
Insulin n (%)
8 (8.3)
14 (14.3)
13 (14.0)
14 (14.7)
0.505
Sulfonylureas n (%)
37 (38.5)
32 (32.7)
34 (36.6)
30 (31.6)
0.717
Metformin n (%)
38 (39.6)
27 (27.6)
24 (25.8)
22 (23.2)
0.062
Acarbose n (%)
23 (24.0)
28 (28.6)
28 (30.1)
31 (32.6)
0.602
Insulin secretagogues n (%)
18 (18.8)
19 (19.4)
20 (21.5)
22 (23.2)
0.870
Fibrinogen (mg/dl) -1
Data are expressed as means (SD) or median (inter-quartile range) or percentage. Abbreviations: see in Table 1 p value was calculated by one-way ANOVA test or Kruskal–Wallis H or Chi-square test
fibrinogen levels, and reduced HDL levels compared to the subjects without DM. However, age, sex, BMI, smoking, drinking, eGFR, hematocrit, hemoglobin, hypertension, and current use of statins and aspirin in two groups were not significantly different. The clinical and biochemical characteristics of subjects with DM according to WBV (3 s-1) quartiles are shown in Table 2. There was a significant difference in TG, HDL, FPG, HbA1c, fibrinogen, and WBV (200 s-1) levels. However, mean age, BMI, SBP, DBP, TC, LDL, eGFR, hemoglobin, hematocrit, plasma viscosity, DM duration, and the percentage of sex, current smokers, drinking, hypertension, and statin use were not significantly different among the subjects with all four WBV (3 s-1) quartiles.
123
The means and SD of baPWV in patients with DM according to WBV (3 s-1) quartiles are shown in Fig. 1. The means of baPWV tend to increase with WBV (3 s-1) quartiles. The means and SD of baPWV are 1,548.7 (102.6) in Q1, 1,567.6 (100.4) in Q2, 1,564.2 (114.4) in Q3, and 1,604.2 (97.4) cm/s in Q4, respectively (p = 0.002). The partial correlation between baPWV and rheological parameters are summarized in Table 3. After adjustment for age, sex, BMI, drinking, smoking status, SBP, DBP, FPG, TC, TG, HDL, LDL, eGFR, hemoglobin, statin use, HbA1c, DM duration, and hypertension, WBV 3 s-1 statistically correlated with baPWV only in patients with DM but not in control subjects (for patients with DM, r = 0.285, p = 0.039; for control subjects, r = 0.065, p = 0.251, respectively) (see Fig. 2).
Endocrine
Fig. 1 The means of baPWV according to whole blood viscosity (3 s-1) quartiles in patients with DM. One-way ANOVA test was used to analyze the data according to whole blood viscosity (3 s-1) quartiles Table 3 Partial correlation coefficient (r) for baPWV in relation to rheological parameter levels
WBV 3 s
-1
(mPa s)
WBV 200 s-1 (mPa s) PV (mPa s) Hematocrit (%) Fibrinogen (mg/dl)
Diabetic patients
Control subjects
r
r
P value
P value
0.285
0.039
0.065
0.251
0.176
0.208
0.095
0.096
-0.100 0.060
0.477 0.670
0.023 -0.059
0.683 0.299
0.135
0.337
0.022
0.696
Adjusted for age, sex, BMI, drinking, smoking status, SBP, DBP, FPG, TC, TG, HDL, LDL, eGFR, hemoglobin, statins use, HbA1c, DM duration, and hypertension. Variables such as TG, HDL, and FPG were logarithmically transformed before statistical analysis. Abbreviations: see in Table 1
Stepwise multiple linear regression analysis was performed to assess the correlation between baPWV and rheological parameters in Table 4. Twenty-three variables, including age, sex, BMI, drinking, smoking status, SBP, DBP, TC, TG, HDL, LDL, WBV (3 s-1), WBV (200 s-1), plasma viscosity, hematocrit, fibrinogen, hemoglobin, statin use, eGFR, FPG, HbA1c, DM duration, and hypertension entered into the original multivariate model. The results showed that age, SBP, WBV (3 s-1), HDL, and HbA1c were correlated with baPWV in patients with DM and TC and SBP were correlated with baPWV in control subjects. Notably, WBV (3 s-1) was found to be a significant determinant for increased baPWV in patients with DM (b = 0.184; P \ 0.001).
Discussion In this study, we found that the participants with DM had higher WBV levels (3 s-1) than those without DM.
Moreover, baPWV elevated as WBV (3 s-1) increased in DM. Multiple regression analysis further revealed that WBV (3 s-1) is an independent and significant determinant for elevated baPWV in DM. Our results suggest that WBV (3 s-1) may play a potential role in the development and progression of atherosclerosis in DM. Our study indicated that serum WBV at low shear rate has a tight correlation with baPWV in DM. There are several plausible mechanisms for the abnormalities of blood viscosity and the accelerated arterial stiffness in diabetic patients. Firstly, the development and progression of insulin resistance play a key role in DM. Moreover, insulin resistance and metabolic syndrome are associated with hyperviscosity syndrome [24]. Plasma viscosity is a significant determinant of endothelial function and plays an important role in the maintenance of normal vascular resistance [25]. The fluctuations in WBV at low shear rate directly determine endothelial shear stress, which is a key factor in the development of atherosclerosis. Increased WBV has been shown to lead to vascular remodeling, altered lipid metabolism, and endothelial inflammation [26]. DM contributes to atherogenesis by inducing endothelial cell injury and dysfunction [27]. Nitric oxide (NO) is produced by vascular endothelial cells and participates in the maintenance of vascular tone. Reduced NO synthesis caused by endothelial dysfunction contributes to arterial stiffness [28]. An inverse relationship is observed between the reduction in NO bioavailability in endothelial progenitor cells and the patient’s plasma glucose and glycated hemoglobin levels [29]. In addition, NO modulates red blood cell’s membrane deformability, and at the same time red blood cells modulate NO bioavailability [30]. Secondly, low-grade chronic inflammation plays a key role in DM. It has been observed that low-grade chronic inflammation induces vascular damages [31]. Some inflammatory markers, such as C-reactive protein and leukocyte count, are reported to have positive correlations with blood viscosity [32]. In addition, increased blood viscosity is linked with metabolic syndrome, hypertension, CHD, and stroke, which are all relevant to chronic inflammation [32–35]. Finally, DM is closely associated with central obesity, hypertension, and abnormal lipid profiles. A cluster of risk factors accelerates the progression of atherosclerosis under a state of insulin resistance. Recent studies found that insulin resistance is associated with hyperviscosity syndrome [24, 36]. In addition, a number of studies have reported that WBV is positively correlated with LDL cholesterol and TG concentrations, and negatively correlated with HDL-cholesterol [37, 38]. Smoking, dyslipidemia, obesity, insulin resistance, and high viscosity accelerate the development of atherosclerosis in a synergistic fashion.
123
Endocrine Fig. 2 WBV 3 s-1 levels are positively correlated with baPWV in patients with DM. A significant correlation was found using partial correlation
Table 4 Stepwise multivariate linear regression analysis with baPWV (cm/s) as the dependent variable Variables
b
p value
Control subjects TC (mmol/L)
0.158
0.007
SBP (mmHg)
0.164
0.023
SBP (mmHg) WBV 3 s-1 (mPa s)
0.477 0.184
\0.001 \0.001
Hemoglobin A1c (%)
0.142
0.001
0.102
0.015
-0.084
0.045
Diabetic patients
Age (years) HDL (mmol/L)
TG, HDL, and FPG were log-transformed before statistical analysis b standardized regression coefficient, baPWV brachial-ankle pulse wave velocity, SBP systolic blood pressure, WBV whole blood viscosity, TC total cholesterol, HDL high-density lipoprotein cholesterol The p value for entry was set at 0.05, and the p value for removal was set at 0.10. Adjusted R2 = 0.367, p \ 0.001 for diabetic patients and adjusted R2 = 0.287, p \ 0.001 for control subjects, respectively
The present study had several limitations. First, based on the cross-sectional study design, the present findings are inherently limited in the ability to eliminate causal relationships between WBV and baPWV. Second, since some of the study population had several risk factors including hypertension and dyslipidemia, we could not eliminate the possible effects of underlying diseases and medications used for these diseases on the present results. Further prospective population-based studies are needed to
123
investigate the mechanisms in order to answer these questions. Third, the study is lacking in information about serum insulin level and inflammatory markers linking WBV at low shear rate and baPWV in DM. In conclusion, the present study showed that baPWV increased as WBV (3 s-1) elevated in DM. Moreover, WBV (3 s-1) is independently associated with baPWV even after adjusting other cardiovascular risk factors. Early detection of abnormal WBV levels at low shear rate should warrant for early search of undetected arterial stiffness in patients with DM. Acknowledgments This study was supported by China Postdoctoral Science Foundation (No. 2013M541409) and Technology Foundation for Selected Overseas Chinese Scholar, Ministry of Personnel of China (No. 2013578). Conflict of interest
None.
References 1. N. Sarwar, P. Gao, S.R. Seshasai, R. Gobin, S. Kaptoge, A.E. Di, E. Ingelsson, D.A. Lawlor, E. Selvin, M. Stampfer, C.D. Stehouwer, S. Lewington, L. Pennells, A. Thompson, N. Sattar, I.R. White, K.K. Ray, J. Danesh, Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet 375, 2215–2222 (2010) 2. S.R. Seshasai, S. Kaptoge, A. Thompson, A.E. Di, P. Gao, N. Sarwar, P.H. Whincup, K.J. Mukamal, R.F. Gillum, I. Holme, I. Njolstad, A. Fletcher, P. Nilsson, S. Lewington, R. Collins, V. Gudnason, S.G. Thompson, N. Sattar, E. Selvin, F.B. Hu, J.
Endocrine
3.
4.
5.
6.
7.
8. 9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
Danesh, Diabetes mellitus, fasting glucose, and risk of causespecific death. N. Engl. J. Med. 364, 829–841 (2011) A.J. Garber, Attenuating CV risk factors in patients with diabetes: clinical evidence to clinical practice. Diabetes Obes. Metab. 4(Suppl 1), S5–S12 (2002) G.W. Davison, T. Ashton, L. George, I.S. Young, J. McEneny, B. Davies, S.K. Jackson, J.R. Peters, D.M. Bailey, Molecular detection of exercise-induced free radicals following ascorbate prophylaxis in type 1 diabetes mellitus: a randomised controlled trial. Diabetologia 51, 2049–2059 (2008) E.U. Nwose, E. Butkowski, N. Cann, Whole blood viscosity determination in diabetes management: perspective in practice. N. Am. J. Med. Sci. 1, 110–113 (2009) R.B. Paisey, J. Harkness, M. Hartog, T. Chadwick, The effect of improvement in diabetic control on plasma and whole blood viscosity. Diabetologia 19, 345–349 (1980) A. Redheuil, W.C. Yu, C.O. Wu, E. Mousseaux, A. de Cesare, R. Yan, N. Kachenoura, D. Bluemke, J.A. Lima, Reduced ascending aortic strain and distensibility: earliest manifestations of vascular aging in humans. Hypertension 55, 319–326 (2010) M.F. O’Rourke, S.S. Franklin, Arterial stiffness: reflections on the arterial pulse. Eur. Heart J. 27, 2497–2498 (2006) J. Blacher, A.D. Protogerou, O. Henry, S. Czernichow, P. Iaria, Y. Zhang, D. Agnoletti, M.E. Safar, Aortic stiffness, inflammation, denutrition and type 2 diabetes in the elderly. Diabetes. Metab. 38, 68–75 (2012) A.S. Mansour, A. Yannoutsos, N. Majahalme, D. Agnoletti, M.E. Safar, S. Ouerdane, J. Blacher, Aortic stiffness and cardiovascular risk in type 2 diabetes. J. Hypertens. 31, 1584–1592 (2013) C. Carallo, C. Irace, M.S. De Franceschi, F. Coppoletta, R. Tiriolo, C. Scicchitano, F. Scavelli, A. Gnasso, The effect of aging on blood and plasma viscosity. An 11.6 years follow-up study. Clin. Hemorheol. Microcirc. 47, 67–74 (2011) I. Velcheva, N. Antonova, E. Titianova, P. Damianov, N. Dimitrov, I. Ivanov, Hemorheological parameters in correlation with the risk factors for carotid atherosclerosis. Clin. Hemorheol. Microcirc. 35, 195–198 (2006) M. Wiewiora, K. Sosada, L. Slowinska, J. Piecuch, M. Gluck, W. Zurawinski, B. Turczynski, Sex-dependent differences in rheological properties and the relation of blood viscosity to erythrocyte aggregation indices among morbidly obese patients. Clin. Hemorheol. Microcirc. 44, 259–267 (2010) J. Danesh, R. Collins, R. Peto, G.D. Lowe, Haematocrit, viscosity, erythrocyte sedimentation rate: meta-analyses of prospective studies of coronary heart disease. Eur. Heart J. 21, 515–520 (2000) G.D. Lowe, F.G. Fowkes, J. Dawes, P.T. Donnan, S.E. Lennie, E. Housley, Blood viscosity, fibrinogen, and activation of coagulation and leukocytes in peripheral arterial disease and the normal population in the Edinburgh Artery Study. Circulation 87, 1915–1920 (1993) G.D. Lowe, A.J. Lee, A. Rumley, J.F. Price, F.G. Fowkes, Blood viscosity and risk of cardiovascular events: the Edinburgh Artery Study. Br. J. Haematol. 96, 168–173 (1997) A. Hoieggen, E. Fossum, A. Moan, E. Enger, S.E. Kjeldsen, Whole-blood viscosity and the insulin-resistance syndrome. J. Hypertens. 16, 203–210 (1998) D.C. Le, T. Khodabandehlou, M. Vimeux, Impaired hemorheological properties in diabetic patients with lower limb arterial ischaemia. Clin. Hemorheol. Microcirc. 25, 43–48 (2001) D.C. Le, M. Vimeux, T. Khodabandehlou, Blood rheology in patients with diabetes mellitus. Clin. Hemorheol. Microcirc. 30, 297–300 (2004) F. Jung, From hemorheology to microcirculation and regenerative medicine: Fahraeus Lecture 2009. Clin. Hemorheol. Microcirc. 45, 79–99 (2010)
21. K.U. Eckardt, J.S. Berns, M.V. Rocco, B.L. Kasiske, Definition and classification of CKD: the debate should be about patient prognosis—a position statement from KDOQI and KDIGO. Am. J. Kidney Dis. 53, 915–920 (2009) 22. R.T. Wang, Y. Li, X.Y. Zhu, Y.N. Zhang, Increased mean platelet volume is associated with arterial stiffness. Platelets 22, 447–451 (2011) 23. R.Y. Li, Z.G. Cao, J.R. Zhang, Y. Li, R.T. Wang, Decreased serum bilirubin is associated with silent cerebral infarction. Arterioscler. Thromb. Vasc. Biol. 34, 946–951 (2014) 24. J.F. Brun, E. Varlet-Marie, R. de Mauverger, J. Mercier, Minimal model-derived insulin sensitivity, insulin secretion and glucose tolerance: relationships with blood rheology. Clin. Hemorheol. Microcirc. 51, 21–27 (2012) 25. A.G. Tsai, C. Acero, P.R. Nance, P. Cabrales, J.A. Frangos, D.G. Buerk, M. Intaglietta, Elevated plasma viscosity in extreme hemodilution increases perivascular nitric oxide concentration and microvascular perfusion. Am. J. Physiol. Heart Circ. Physiol. 288, H1730–H1739 (2005) 26. H.A. Silber, D.A. Bluemke, P. Ouyang, Y.P. Du, W.S. Post, J.A. Lima, The relationship between vascular wall shear stress and flow-mediated dilation. J. Am. Coll. Cardiol. 38, 1859–1865 (2001) 27. S. Hamed, B. Brenner, A. Roguin, Nitric oxide: a key factor behind the dysfunctionality of endothelial progenitor cells in diabetes mellitus type-2. Cardiovasc. Res. 91, 9–15 (2011) 28. J. Bellien, J. Favre, M. Iacob, J. Gao, C. Thuillez, V. Richard, R. Joannides, Arterial stiffness is regulated by nitric oxide and endothelium-derived hyperpolarizing factor during changes in blood flow in humans. Hypertension 55, 674–680 (2010) 29. S. Hamed, B. Brenner, A. Aharon, D. Daoud, A. Roguin, Nitric oxide and superoxide dismutase modulate endothelial progenitor cell function in type 2 diabetes mellitus. Cardiovasc. Diabetol. 8, 56 (2009) 30. S. Forconi, T. Gori, Endothelium and hemorheology. Clin. Hemorheol. Microcirc. 53, 3–10 (2013) 31. M. Charakida, F. O’Neil, S. Masi, N. Papageorgiou, D. Tousoulis, Inflammatory disorders and atherosclerosis: new therapeutic approaches. Curr. Pharm. Des. 17, 4111–4120 (2011) 32. A. Vaya, A. Hernandez-Mijares, E. Bonet, R. Sendra, E. Sola, R. Perez, D. Corella, B. Laiz, Association between hemorheological alterations and metabolic syndrome. Clin. Hemorheol. Microcirc. 49, 493–503 (2011) 33. A. Damaske, S. Muxel, F. Fasola, M.C. Radmacher, S. Schaefer, A. Jabs, D. Orphal, P. Wild, J.D. Parker, M. Fineschi, T. Munzel, S. Forconi, T. Gori, Peripheral hemorheological and vascular correlates of coronary blood flow. Clin. Hemorheol. Microcirc. 49, 261–269 (2011) 34. E.A. Olausson, A. Kilander, Glycaemic index of modified cornstarch in solutions with different viscosity. A study in subjects with diabetes mellitus type 2. Clin. Nutr. 27, 254–257 (2008) 35. I.A. Tikhomirova, A.O. Oslyakova, S.G. Mikhailova, Microcirculation and blood rheology in patients with cerebrovascular disorders. Clin. Hemorheol. Microcirc. 49, 295–305 (2011) 36. J.F. Brun, E. Varlet-Marie, R.E. de Mauverger, Relationships between insulin sensitivity measured with the oral minimal model and blood rheology. Clin. Hemorheol. Microcirc. 51, 29–34 (2012) 37. G. de Simone, R.B. Devereux, S. Chien, M.H. Alderman, S.A. Atlas, J.H. Laragh, Relation of blood viscosity to demographic and physiologic variables and to cardiovascular risk factors in apparently normal adults. Circulation 81, 107–117 (1990) 38. G.D. Sloop, D.W. Garber, The effects of low-density lipoprotein and high-density lipoprotein on blood viscosity correlate with their association with risk of atherosclerosis in humans. Clin. Sci. 92, 473–479 (1997)
123
ORIGINAL ARTICLE
Association between whole blood viscosity and arterial stiffness in patients with type 2 diabetes mellitus Ying Li • Xiu-xia Tian • Tiemin Liu Rui-tao Wang
•
Received: 16 May 2014 / Accepted: 9 October 2014 Ó Springer Science+Business Media New York 2014
Abstract Type 2 diabetes mellitus (DM) carries an increased risk for cardiovascular complications. The brachial-ankle pulse wave velocity (baPWV) is an index for early atherosclerotic changes. Recently, the effect of altered blood rheology on atherosclerosis has received attention. Therefore, this study aimed to examine the association of hemorheological parameters with baPWV in patients with DM. In this cross-sectional study, we investigated the relationship between rheological parameters and baPWV in 323 control subjects (160 men and 163 women) and 382 patients with DM (170 men and 212 women). The participants with DM had higher whole blood viscosity (WBV) levels both at low shear rate (3 s-1) and at high shear rate (200 s-1) than those without DM. Different metabolic parameters were compared across WBV (3 s-1) quartiles. The mean values of baPWV gradually increased with WBV (3 s-1) quartiles. In addition, there was a positive correlation between baPWV and WBV 3 s-1 in patients with DM after adjusting confounding factors (r = 0.285, p = 0.039). Stepwise multiple linear regression analysis further revealed that WBV (3 s-1) is a
Y. Li X. Tian R. Wang (&) Department of Geriatrics, The Second Affiliated Hospital, Harbin Medical University, NO. 246 Xuefu ST, Nangang District, Harbin 150086, Heilongjiang, China e-mail: [email protected] Y. Li International Physical Examination and Healthy Center, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang, China T. Liu Division of Hypothalamic Research, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX 75390, USA
significant determinant for increased baPWV in DM (b = 0.184; p \ 0.001). However, there were no association between WBV (3 s-1) and baPWV in control subjects. The findings showed that baPWV increased as WBV (3 s-1) elevated in DM. Moreover, WBV (3 s-1) is independently associated with baPWV even after adjusting other cardiovascular risk factors. Early detection of abnormal WBV levels at low shear rate should warrant for early search of undetected arterial stiffness in patients with DM. Keywords Type 2 diabetes mellitus Whole blood viscosity Brachial-ankle pulse wave velocity Arterial stiffness
Introduction Type 2 diabetes mellitus (DM) is associated with an increased risk of stroke and coronary heart disease (CHD) and non-vascular mortality [1, 2]. The occurrence of insulin resistance accompanied with hyperviscosity worsens the state of atherosclerosis in patients with DM. Furthermore, both DM and hyperviscosity have the tendency to develop thrombosis [3]. Recent studies demonstrated that hyperviscosity in DM is strongly influenced by the excellence of glycemic control [4–6]. Arterial stiffness due to decreased arterial compliance is one of the major signs of vascular aging [7]. Elevated arterial stiffness, an indicator of subclinical atherosclerosis, is associated with myocardial infarction, heart failure, stroke, renal disease, and all-cause mortality [8]. Brachialankle pulse wave velocity (baPWV) measurement, a simple, non-invasive, and automated measurement method, reflects the stiffness of muscular arteries and is widely used
123
Endocrine
as an index of arterial stiffness and vascular damage. Moreover, recent reports revealed that PWV is a forceful independent marker of cardiovascular disease and a powerful determinant of total mortality in diabetic patients [9, 10]. Altered hemorheological parameters play a key role in atherogenesis. Many cardiovascular risk factors, including aging, obesity, carotid intima-media thickness, are linked with changes of rheological parameters [11–13]. The risk of acute myocardial infarction and cardiovascular death increases with elevations in whole blood viscosity (WBV) [14, 15]. A recent study confirmed that WBV is a predictor of cardiovascular events [16]. In addition, marked hemorheological impairments were observed in diabetic patients and a high WBV is associated with increased insulin resistance [17–19]. Based on the assumption that both baPWV and hemorheological parameters are related to cardiovascular disease and both hemorheological parameters and vascular tone cooperate in regulating microvascular perfusion [20], we postulated that there would be a close relationship between the levels of baPWV and hemorheological parameters. Therefore, the aim of the study was to examine if rheological parameters are independently associated with baPWV in patients with DM.
Research design and methods Study population We studied 705 randomly selected subjects who visited International Physical Examination and Healthy Center, Harbin, China, from January 2009 through December 2010. This is a cross-sectional study and there are 382 patients with DM and 323 control subjects. Control subjects were matched for age, sex, body mass index (BMI), and smoking status. The participants generally underwent health status examination every 1 year. There were 375 (53.2 %) women and 330 (46.8 %) men in our study. The mean ages were 56.3 ± 5.9 and 56.8 ± 6.2 years, respectively. We obtained informed consent from all subjects. The study protocol was approved by the Ethics Committee of the Second Hospital of Harbin Medical University, China.
position using an automated sphygmomanometer, after a 15-min rest period. The mean systolic and diastolic blood pressure was calculated after two measurements. The BMI was calculated as the weight (kg) divided by the square of the height (m2).
Biochemical analyses Fasting venous blood samples were collected for the analysis. The values included total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL), lowdensity lipoprotein cholesterol (LDL), and fasting plasma glucose (FPG). All assays were conducted at the Laboratory of Analytical Biochemistry at the Second Hospital of Harbin Medical University, Harbin, using a biochemical analyzer (Modular Analytics, Roche, Mannheim, Germany). The HbA1c level was measured using high-performance liquid chromatography by HbA1c analyzer (VariantTM II; BioRad, Hercules, CA, USA). Hemoglobin was determined with an autoanalyzer (Sysmex XE-2100, Kobe, Japan). WBV was determined at shear rates between 3 and 200 s-1 corrected hematocrit of 45 % at 37 °C using a viscometer (Succeeder SA-9000, Beijing, China). For high shear rate, the intra- and inter-assay coefficient variations were 2.7 and 5.6 %, respectively. For low shear rate, the intra- and interassay coefficient variations were 4.6 and 9.8 %, respectively. Plasma viscosity was measured by Harkness method and hematocrit was evaluated by microcentrifugation. Plasma fibrinogen concentrations were assayed on the Beckman Coulter ACL-TOP analyzer (Instrumentation Laboratory, Lexingtion, MA, USA). All measurements were performed within 2 h of sampling. DM was defined as fasting serum glucose was C7.0 mmol/L or non-fasting serum glucose was C11.1 mmol/L or as taking prescription medications. For the subjects with impaired fasting glucose, DM was diagnosed if a 2-h postglucose level after a 75-g oral glucose tolerance test C11.1 mmol/L. Hypertension was defined as taking antihypertensive medication or having blood pressure 140/90 mmHg at the initial examinations. The Modification of Diet in Renal Disease (MDRD) equation was used to estimate glomerular filtration rate (eGFR). MDRD equation was eGFR = 186.3 9 (SCr)-1.154 9 (age)-0.203(9 0.742 if female) [21].
Clinical examination Exclusion criteria Clinical data, including medical history, smoking status, and medication use were recorded for each participant. All the subjects underwent physical examination which included anthropometric and blood pressure measurements. Blood pressure was measured in the right arm in the seated
123
Exclusion criteria include tumor, autoimmune diseases, rheumatoid arthritis, hematological disorders, chronic liver and kidney diseases, infection, cancer, CHD, atrial fibrillation, and stroke.
Endocrine Table 1 Characteristics of the analyzed participants according to DM status
Variables N
DM type 2 diabetes mellitus, BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, TC total cholesterol, TG triglyceride, HDL high-density lipoprotein cholesterol, LDL low-density lipoprotein cholesterol, FPG fasting plasma glucose, baPWV brachial-ankle pulse wave velocity, eGFR estimated glomerular filtration rate, WBV whole blood viscosity, PV plasma viscosity, ACEI angiotensin-converting enzyme inhibitor, ARB angiotensin II receptor antagonist, CCB calcium channel blocker p value was calculated by the student’s t test or Mann– Whitney U test or Chi-square test
382
Without DM
P value
323
Age (year)
56.8 (6.0)
56.2 (6.0)
Sex (male, %)
170 (44.5)
160 (49.5)
0.182
BMI (kg/m2)
25.4 (3.0)
25.1 (3.0)
0.147
Smoker (n, %)
101 (26.4)
Drinking (n, %) Data are shown as means (SD) or median (inter-quartile range) or percentage
With DM
SBP (mmHg)
78 (24.1)
0.149
0.486
97 (25.4)
85 (26.3)
0.780
135.7 (13.0)
132.1 (10.4)
\0.001
DBP (mmHg)
82.2 (6.7)
79.5 (7.8)
\0.001
TC (mmol/L)
5.62 (0.89)
4.85 (0.80)
\0.001
TG (mmol/L)
3.04 (2.47–3.65)
2.36 (1.94–2.83)
\0.001
HDL (mmol/L)
1.27 (1.11–1.44)
1.52 (1.33–1.71)
\0.001
LDL (mmol/L)
2.70 (0.72)
2.41 (0.70)
\0.001
FPG (mmol/L)
6.56 (6.14–6.96)
5.15 (4.85–5.51)
\0.001
Hemoglobin A1c (%)
7.51 (0.87)
4.80 (0.43)
\0.001
73.8 (16.2) 1571.1 (105.4)
75.4 (12.4) 1428.9 (102.5)
0.117 \0.001
125.0 (10.9)
123.9 (10.7)
47.4 (3.3)
47.1 (4.3)
Fibrinogen (mg/dl)
367.9 (63.7)
333.5 (69.8)
WBV 3 s-1 (mPa s)
eGFR (mL/min/1.73 m2) BaPWV (cm/s) Hemoglobin (g/dl) Hematocrit (%)
0.132 0.316 \0.001
10.15 (1.35)
8.56 (0.90)
\0.001
WBV 200 s-1 (mPa s)
6.50 (0.36)
5.61 (0.37)
\0.001
PV (mPa s)
1.60 (0.08)
1.53 (0.08)
\0.001
Hypertension n (%)
145 (38.0)
109 (33.7)
0.246
ACEIs/ARBs n (%)
73 (19.1)
67 (20.7)
0.588
CCBs n (%)
70 (18.3)
63 (19.5)
0.690
Statins n (%)
87 (22.8)
58 (17.9)
0.115
Aspirin n (%)
43 (11.3)
26 (8.0)
Measurement of BaPWV BaPWV was measured using an automatic device (model MB3000, M&B Electronic Instruments, Beijing, China). The subjects rested in the supine position for 5 min. The baPWV was automatically calculated according to the formula (L/PTT). L is the difference between the length from heart to ankle and the length from heart to brachium. PTT was the pulse transit time between the brachial and tibial arterial waveforms. Mean right and left baPWV value was calculated during analysis. All measurements were conducted by a single examiner who was blinded to the clinical data. The method was validated in a previous report [22, 23].
0.153
H was used for continuous variables among multiple groups. Correlations between baPWV and rheological parameters were tested by partial correlation. Stepwise multiple linear regression analysis was performed to assess the correlation between baPWV and WBV (3 s-1). The participants with DM were classified into quartiles by their WBV (3 s-1) levels. The WBV (3 s-1) quartiles were Q1 (B9.06 mPa s), Q2 (9.07–9.79 mPa s), Q3 (9.80–10.88 mPa s), and Q4 (C10.89 mPa s). Variables such as TG, HDL, and FPG were logarithmically transformed before statistical analysis to approximate a normal distribution. Values at p \ 0.05 were considered to be statistically significant. Statistical analyses were conducted using the SPSS software package version 17.0 (SPSS Inc., Chicago, IL, USA).
Statistical analysis Results All data were expressed as mean ± SD or median (IQR) or percentage. The Chi-square statistical test was used for categorical variables, while the student’s t test or Mann– Whitney U test was used for continuous variables between the two groups and one-way ANOVA or Kruskal–Wallis
The clinical and laboratory characteristics of all participants are shown in Table 1. The patients with DM had higher SBP, DBP, TG, TC, LDL, FPG, HbA1c, baPWV, WBV (3 s-1), WBV (200 s-1), plasma viscosity,
123
Endocrine Table 2 Clinical and biochemical characteristics of subjects with DM Quartiles of WBV (3 s-1) Q1 N
Q2 96
Age (years)
57.1 (6.0)
Sex (male, %)
46 (47.9)
2
BMI (kg/m )
25.0 (3.4)
Q3 98
Q4 93
56.7 (6.1)
56.6 (5.9)
48 (49.0)
95 56.9 (6.3)
35 (37.6)
25.5 (3.1)
25.5 (2.8)
P value
41 (43.2) 25.8 (2.6)
0.958 0.377 0.369
Smoker (n, %)
21 (21.9)
33 (33.7)
23 (24.7)
24 (25.3)
0.276
Drinking (n, %)
26 (27.1)
28 (28.6)
17 (18.3)
25 (26.3)
0.362
134.6 (14.0) 81.3 (6.9)
135.5 (13.0) 82.4 (6.3)
134.3 (11.6) 81.4 (6.6)
138.6 (13.0) 83.6 (6.9)
0.089 0.059
SBP (mmHg) DBP (mmHg) FPG (mmol/L)
6.53 (6.18–6.84)
6.41 (6.03–6.89)
6.63 (6.20–7.00)
6.67 (6.26–7.28)
0.015
TC (mmol/L)
5.52 (0.97)
5.58 (0.85)
5.62 (0.91)
5.75 (0.81)
0.323
TG (mmol/L)
2.83 (2.32–3.35)
3.03 (2.50–3.99)
3.15 (2.65–3.77)
3.12 (2.56–4.06)
0.021
HDL (mmol/L)
1.35 (1.20–1.49)
1.26 (1.09–1.46)
1.23 (1.07–1.38)
1.25 (1.10–1.43)
0.011
2.58 (0.79)
2.63 (0.71)
2.75 (0.63)
2.84 (0.73)
0.053
75.5 (16.1)
74.2 (16.5)
73.9 (15.7)
71.5 (16.3)
0.381
7.3 (0.8)
7.5 (1.0)
7.6 (0.8)
7.6 (0.8)
0.044
LDL (mmol/L) 2
eGFR (mL/min/1.73 m ) Hemoglobin A1c (%) DM duration (years) Hemoglobin (g/dl) Hematocrit (%)
2.3 (1.0)
2.3 (1.1)
2.5 (1.3)
2.5 (1.2)
0.617
123.3 (11.5)
125.0 (10.7)
125.0 (10.5)
126.8 (10.8)
0.184
47.2 (3.7)
47.3 (3.0)
47.4 (3.3)
47.7 (3.2)
0.795
357.0 (71.5)
363.6 (52.2)
365.5 (63.8)
385.6 (63.4)
0.013
WBV200 s (mPa s)
6.41 (0.35)
6.50 (0.35)
6.49 (0.36)
6.60 (0.36)
0.003
PV (mPa s)
1.59 (0.08)
1.60 (0.08)
1.60 (0.09)
1.61 (0.08)
0.875
Hypertension n (%) Statins n (%)
33 (34.4) 20 (20.8)
32 (32.7) 24 (24.5)
38 (40.9) 17 (18.3)
39 (41.1) 26 (27.4)
0.506 0.461
ACEIs/ARBs n (%)
16 (16.7)
16 (16.3)
17 (18.3)
21 (22.1)
0.718
CCBs n (%)
15 (15.6)
13 (13.3)
20 (21.5)
17 (17.9)
0.478
Insulin n (%)
8 (8.3)
14 (14.3)
13 (14.0)
14 (14.7)
0.505
Sulfonylureas n (%)
37 (38.5)
32 (32.7)
34 (36.6)
30 (31.6)
0.717
Metformin n (%)
38 (39.6)
27 (27.6)
24 (25.8)
22 (23.2)
0.062
Acarbose n (%)
23 (24.0)
28 (28.6)
28 (30.1)
31 (32.6)
0.602
Insulin secretagogues n (%)
18 (18.8)
19 (19.4)
20 (21.5)
22 (23.2)
0.870
Fibrinogen (mg/dl) -1
Data are expressed as means (SD) or median (inter-quartile range) or percentage. Abbreviations: see in Table 1 p value was calculated by one-way ANOVA test or Kruskal–Wallis H or Chi-square test
fibrinogen levels, and reduced HDL levels compared to the subjects without DM. However, age, sex, BMI, smoking, drinking, eGFR, hematocrit, hemoglobin, hypertension, and current use of statins and aspirin in two groups were not significantly different. The clinical and biochemical characteristics of subjects with DM according to WBV (3 s-1) quartiles are shown in Table 2. There was a significant difference in TG, HDL, FPG, HbA1c, fibrinogen, and WBV (200 s-1) levels. However, mean age, BMI, SBP, DBP, TC, LDL, eGFR, hemoglobin, hematocrit, plasma viscosity, DM duration, and the percentage of sex, current smokers, drinking, hypertension, and statin use were not significantly different among the subjects with all four WBV (3 s-1) quartiles.
123
The means and SD of baPWV in patients with DM according to WBV (3 s-1) quartiles are shown in Fig. 1. The means of baPWV tend to increase with WBV (3 s-1) quartiles. The means and SD of baPWV are 1,548.7 (102.6) in Q1, 1,567.6 (100.4) in Q2, 1,564.2 (114.4) in Q3, and 1,604.2 (97.4) cm/s in Q4, respectively (p = 0.002). The partial correlation between baPWV and rheological parameters are summarized in Table 3. After adjustment for age, sex, BMI, drinking, smoking status, SBP, DBP, FPG, TC, TG, HDL, LDL, eGFR, hemoglobin, statin use, HbA1c, DM duration, and hypertension, WBV 3 s-1 statistically correlated with baPWV only in patients with DM but not in control subjects (for patients with DM, r = 0.285, p = 0.039; for control subjects, r = 0.065, p = 0.251, respectively) (see Fig. 2).
Endocrine
Fig. 1 The means of baPWV according to whole blood viscosity (3 s-1) quartiles in patients with DM. One-way ANOVA test was used to analyze the data according to whole blood viscosity (3 s-1) quartiles Table 3 Partial correlation coefficient (r) for baPWV in relation to rheological parameter levels
WBV 3 s
-1
(mPa s)
WBV 200 s-1 (mPa s) PV (mPa s) Hematocrit (%) Fibrinogen (mg/dl)
Diabetic patients
Control subjects
r
r
P value
P value
0.285
0.039
0.065
0.251
0.176
0.208
0.095
0.096
-0.100 0.060
0.477 0.670
0.023 -0.059
0.683 0.299
0.135
0.337
0.022
0.696
Adjusted for age, sex, BMI, drinking, smoking status, SBP, DBP, FPG, TC, TG, HDL, LDL, eGFR, hemoglobin, statins use, HbA1c, DM duration, and hypertension. Variables such as TG, HDL, and FPG were logarithmically transformed before statistical analysis. Abbreviations: see in Table 1
Stepwise multiple linear regression analysis was performed to assess the correlation between baPWV and rheological parameters in Table 4. Twenty-three variables, including age, sex, BMI, drinking, smoking status, SBP, DBP, TC, TG, HDL, LDL, WBV (3 s-1), WBV (200 s-1), plasma viscosity, hematocrit, fibrinogen, hemoglobin, statin use, eGFR, FPG, HbA1c, DM duration, and hypertension entered into the original multivariate model. The results showed that age, SBP, WBV (3 s-1), HDL, and HbA1c were correlated with baPWV in patients with DM and TC and SBP were correlated with baPWV in control subjects. Notably, WBV (3 s-1) was found to be a significant determinant for increased baPWV in patients with DM (b = 0.184; P \ 0.001).
Discussion In this study, we found that the participants with DM had higher WBV levels (3 s-1) than those without DM.
Moreover, baPWV elevated as WBV (3 s-1) increased in DM. Multiple regression analysis further revealed that WBV (3 s-1) is an independent and significant determinant for elevated baPWV in DM. Our results suggest that WBV (3 s-1) may play a potential role in the development and progression of atherosclerosis in DM. Our study indicated that serum WBV at low shear rate has a tight correlation with baPWV in DM. There are several plausible mechanisms for the abnormalities of blood viscosity and the accelerated arterial stiffness in diabetic patients. Firstly, the development and progression of insulin resistance play a key role in DM. Moreover, insulin resistance and metabolic syndrome are associated with hyperviscosity syndrome [24]. Plasma viscosity is a significant determinant of endothelial function and plays an important role in the maintenance of normal vascular resistance [25]. The fluctuations in WBV at low shear rate directly determine endothelial shear stress, which is a key factor in the development of atherosclerosis. Increased WBV has been shown to lead to vascular remodeling, altered lipid metabolism, and endothelial inflammation [26]. DM contributes to atherogenesis by inducing endothelial cell injury and dysfunction [27]. Nitric oxide (NO) is produced by vascular endothelial cells and participates in the maintenance of vascular tone. Reduced NO synthesis caused by endothelial dysfunction contributes to arterial stiffness [28]. An inverse relationship is observed between the reduction in NO bioavailability in endothelial progenitor cells and the patient’s plasma glucose and glycated hemoglobin levels [29]. In addition, NO modulates red blood cell’s membrane deformability, and at the same time red blood cells modulate NO bioavailability [30]. Secondly, low-grade chronic inflammation plays a key role in DM. It has been observed that low-grade chronic inflammation induces vascular damages [31]. Some inflammatory markers, such as C-reactive protein and leukocyte count, are reported to have positive correlations with blood viscosity [32]. In addition, increased blood viscosity is linked with metabolic syndrome, hypertension, CHD, and stroke, which are all relevant to chronic inflammation [32–35]. Finally, DM is closely associated with central obesity, hypertension, and abnormal lipid profiles. A cluster of risk factors accelerates the progression of atherosclerosis under a state of insulin resistance. Recent studies found that insulin resistance is associated with hyperviscosity syndrome [24, 36]. In addition, a number of studies have reported that WBV is positively correlated with LDL cholesterol and TG concentrations, and negatively correlated with HDL-cholesterol [37, 38]. Smoking, dyslipidemia, obesity, insulin resistance, and high viscosity accelerate the development of atherosclerosis in a synergistic fashion.
123
Endocrine Fig. 2 WBV 3 s-1 levels are positively correlated with baPWV in patients with DM. A significant correlation was found using partial correlation
Table 4 Stepwise multivariate linear regression analysis with baPWV (cm/s) as the dependent variable Variables
b
p value
Control subjects TC (mmol/L)
0.158
0.007
SBP (mmHg)
0.164
0.023
SBP (mmHg) WBV 3 s-1 (mPa s)
0.477 0.184
\0.001 \0.001
Hemoglobin A1c (%)
0.142
0.001
0.102
0.015
-0.084
0.045
Diabetic patients
Age (years) HDL (mmol/L)
TG, HDL, and FPG were log-transformed before statistical analysis b standardized regression coefficient, baPWV brachial-ankle pulse wave velocity, SBP systolic blood pressure, WBV whole blood viscosity, TC total cholesterol, HDL high-density lipoprotein cholesterol The p value for entry was set at 0.05, and the p value for removal was set at 0.10. Adjusted R2 = 0.367, p \ 0.001 for diabetic patients and adjusted R2 = 0.287, p \ 0.001 for control subjects, respectively
The present study had several limitations. First, based on the cross-sectional study design, the present findings are inherently limited in the ability to eliminate causal relationships between WBV and baPWV. Second, since some of the study population had several risk factors including hypertension and dyslipidemia, we could not eliminate the possible effects of underlying diseases and medications used for these diseases on the present results. Further prospective population-based studies are needed to
123
investigate the mechanisms in order to answer these questions. Third, the study is lacking in information about serum insulin level and inflammatory markers linking WBV at low shear rate and baPWV in DM. In conclusion, the present study showed that baPWV increased as WBV (3 s-1) elevated in DM. Moreover, WBV (3 s-1) is independently associated with baPWV even after adjusting other cardiovascular risk factors. Early detection of abnormal WBV levels at low shear rate should warrant for early search of undetected arterial stiffness in patients with DM. Acknowledgments This study was supported by China Postdoctoral Science Foundation (No. 2013M541409) and Technology Foundation for Selected Overseas Chinese Scholar, Ministry of Personnel of China (No. 2013578). Conflict of interest
None.
References 1. N. Sarwar, P. Gao, S.R. Seshasai, R. Gobin, S. Kaptoge, A.E. Di, E. Ingelsson, D.A. Lawlor, E. Selvin, M. Stampfer, C.D. Stehouwer, S. Lewington, L. Pennells, A. Thompson, N. Sattar, I.R. White, K.K. Ray, J. Danesh, Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet 375, 2215–2222 (2010) 2. S.R. Seshasai, S. Kaptoge, A. Thompson, A.E. Di, P. Gao, N. Sarwar, P.H. Whincup, K.J. Mukamal, R.F. Gillum, I. Holme, I. Njolstad, A. Fletcher, P. Nilsson, S. Lewington, R. Collins, V. Gudnason, S.G. Thompson, N. Sattar, E. Selvin, F.B. Hu, J.
Endocrine
3.
4.
5.
6.
7.
8. 9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
Danesh, Diabetes mellitus, fasting glucose, and risk of causespecific death. N. Engl. J. Med. 364, 829–841 (2011) A.J. Garber, Attenuating CV risk factors in patients with diabetes: clinical evidence to clinical practice. Diabetes Obes. Metab. 4(Suppl 1), S5–S12 (2002) G.W. Davison, T. Ashton, L. George, I.S. Young, J. McEneny, B. Davies, S.K. Jackson, J.R. Peters, D.M. Bailey, Molecular detection of exercise-induced free radicals following ascorbate prophylaxis in type 1 diabetes mellitus: a randomised controlled trial. Diabetologia 51, 2049–2059 (2008) E.U. Nwose, E. Butkowski, N. Cann, Whole blood viscosity determination in diabetes management: perspective in practice. N. Am. J. Med. Sci. 1, 110–113 (2009) R.B. Paisey, J. Harkness, M. Hartog, T. Chadwick, The effect of improvement in diabetic control on plasma and whole blood viscosity. Diabetologia 19, 345–349 (1980) A. Redheuil, W.C. Yu, C.O. Wu, E. Mousseaux, A. de Cesare, R. Yan, N. Kachenoura, D. Bluemke, J.A. Lima, Reduced ascending aortic strain and distensibility: earliest manifestations of vascular aging in humans. Hypertension 55, 319–326 (2010) M.F. O’Rourke, S.S. Franklin, Arterial stiffness: reflections on the arterial pulse. Eur. Heart J. 27, 2497–2498 (2006) J. Blacher, A.D. Protogerou, O. Henry, S. Czernichow, P. Iaria, Y. Zhang, D. Agnoletti, M.E. Safar, Aortic stiffness, inflammation, denutrition and type 2 diabetes in the elderly. Diabetes. Metab. 38, 68–75 (2012) A.S. Mansour, A. Yannoutsos, N. Majahalme, D. Agnoletti, M.E. Safar, S. Ouerdane, J. Blacher, Aortic stiffness and cardiovascular risk in type 2 diabetes. J. Hypertens. 31, 1584–1592 (2013) C. Carallo, C. Irace, M.S. De Franceschi, F. Coppoletta, R. Tiriolo, C. Scicchitano, F. Scavelli, A. Gnasso, The effect of aging on blood and plasma viscosity. An 11.6 years follow-up study. Clin. Hemorheol. Microcirc. 47, 67–74 (2011) I. Velcheva, N. Antonova, E. Titianova, P. Damianov, N. Dimitrov, I. Ivanov, Hemorheological parameters in correlation with the risk factors for carotid atherosclerosis. Clin. Hemorheol. Microcirc. 35, 195–198 (2006) M. Wiewiora, K. Sosada, L. Slowinska, J. Piecuch, M. Gluck, W. Zurawinski, B. Turczynski, Sex-dependent differences in rheological properties and the relation of blood viscosity to erythrocyte aggregation indices among morbidly obese patients. Clin. Hemorheol. Microcirc. 44, 259–267 (2010) J. Danesh, R. Collins, R. Peto, G.D. Lowe, Haematocrit, viscosity, erythrocyte sedimentation rate: meta-analyses of prospective studies of coronary heart disease. Eur. Heart J. 21, 515–520 (2000) G.D. Lowe, F.G. Fowkes, J. Dawes, P.T. Donnan, S.E. Lennie, E. Housley, Blood viscosity, fibrinogen, and activation of coagulation and leukocytes in peripheral arterial disease and the normal population in the Edinburgh Artery Study. Circulation 87, 1915–1920 (1993) G.D. Lowe, A.J. Lee, A. Rumley, J.F. Price, F.G. Fowkes, Blood viscosity and risk of cardiovascular events: the Edinburgh Artery Study. Br. J. Haematol. 96, 168–173 (1997) A. Hoieggen, E. Fossum, A. Moan, E. Enger, S.E. Kjeldsen, Whole-blood viscosity and the insulin-resistance syndrome. J. Hypertens. 16, 203–210 (1998) D.C. Le, T. Khodabandehlou, M. Vimeux, Impaired hemorheological properties in diabetic patients with lower limb arterial ischaemia. Clin. Hemorheol. Microcirc. 25, 43–48 (2001) D.C. Le, M. Vimeux, T. Khodabandehlou, Blood rheology in patients with diabetes mellitus. Clin. Hemorheol. Microcirc. 30, 297–300 (2004) F. Jung, From hemorheology to microcirculation and regenerative medicine: Fahraeus Lecture 2009. Clin. Hemorheol. Microcirc. 45, 79–99 (2010)
21. K.U. Eckardt, J.S. Berns, M.V. Rocco, B.L. Kasiske, Definition and classification of CKD: the debate should be about patient prognosis—a position statement from KDOQI and KDIGO. Am. J. Kidney Dis. 53, 915–920 (2009) 22. R.T. Wang, Y. Li, X.Y. Zhu, Y.N. Zhang, Increased mean platelet volume is associated with arterial stiffness. Platelets 22, 447–451 (2011) 23. R.Y. Li, Z.G. Cao, J.R. Zhang, Y. Li, R.T. Wang, Decreased serum bilirubin is associated with silent cerebral infarction. Arterioscler. Thromb. Vasc. Biol. 34, 946–951 (2014) 24. J.F. Brun, E. Varlet-Marie, R. de Mauverger, J. Mercier, Minimal model-derived insulin sensitivity, insulin secretion and glucose tolerance: relationships with blood rheology. Clin. Hemorheol. Microcirc. 51, 21–27 (2012) 25. A.G. Tsai, C. Acero, P.R. Nance, P. Cabrales, J.A. Frangos, D.G. Buerk, M. Intaglietta, Elevated plasma viscosity in extreme hemodilution increases perivascular nitric oxide concentration and microvascular perfusion. Am. J. Physiol. Heart Circ. Physiol. 288, H1730–H1739 (2005) 26. H.A. Silber, D.A. Bluemke, P. Ouyang, Y.P. Du, W.S. Post, J.A. Lima, The relationship between vascular wall shear stress and flow-mediated dilation. J. Am. Coll. Cardiol. 38, 1859–1865 (2001) 27. S. Hamed, B. Brenner, A. Roguin, Nitric oxide: a key factor behind the dysfunctionality of endothelial progenitor cells in diabetes mellitus type-2. Cardiovasc. Res. 91, 9–15 (2011) 28. J. Bellien, J. Favre, M. Iacob, J. Gao, C. Thuillez, V. Richard, R. Joannides, Arterial stiffness is regulated by nitric oxide and endothelium-derived hyperpolarizing factor during changes in blood flow in humans. Hypertension 55, 674–680 (2010) 29. S. Hamed, B. Brenner, A. Aharon, D. Daoud, A. Roguin, Nitric oxide and superoxide dismutase modulate endothelial progenitor cell function in type 2 diabetes mellitus. Cardiovasc. Diabetol. 8, 56 (2009) 30. S. Forconi, T. Gori, Endothelium and hemorheology. Clin. Hemorheol. Microcirc. 53, 3–10 (2013) 31. M. Charakida, F. O’Neil, S. Masi, N. Papageorgiou, D. Tousoulis, Inflammatory disorders and atherosclerosis: new therapeutic approaches. Curr. Pharm. Des. 17, 4111–4120 (2011) 32. A. Vaya, A. Hernandez-Mijares, E. Bonet, R. Sendra, E. Sola, R. Perez, D. Corella, B. Laiz, Association between hemorheological alterations and metabolic syndrome. Clin. Hemorheol. Microcirc. 49, 493–503 (2011) 33. A. Damaske, S. Muxel, F. Fasola, M.C. Radmacher, S. Schaefer, A. Jabs, D. Orphal, P. Wild, J.D. Parker, M. Fineschi, T. Munzel, S. Forconi, T. Gori, Peripheral hemorheological and vascular correlates of coronary blood flow. Clin. Hemorheol. Microcirc. 49, 261–269 (2011) 34. E.A. Olausson, A. Kilander, Glycaemic index of modified cornstarch in solutions with different viscosity. A study in subjects with diabetes mellitus type 2. Clin. Nutr. 27, 254–257 (2008) 35. I.A. Tikhomirova, A.O. Oslyakova, S.G. Mikhailova, Microcirculation and blood rheology in patients with cerebrovascular disorders. Clin. Hemorheol. Microcirc. 49, 295–305 (2011) 36. J.F. Brun, E. Varlet-Marie, R.E. de Mauverger, Relationships between insulin sensitivity measured with the oral minimal model and blood rheology. Clin. Hemorheol. Microcirc. 51, 29–34 (2012) 37. G. de Simone, R.B. Devereux, S. Chien, M.H. Alderman, S.A. Atlas, J.H. Laragh, Relation of blood viscosity to demographic and physiologic variables and to cardiovascular risk factors in apparently normal adults. Circulation 81, 107–117 (1990) 38. G.D. Sloop, D.W. Garber, The effects of low-density lipoprotein and high-density lipoprotein on blood viscosity correlate with their association with risk of atherosclerosis in humans. Clin. Sci. 92, 473–479 (1997)
123
