J Endocrinol Invest DOI 10.1007/s40618-013-0034-9
ORIGINAL ARTICLE
Serum uric acid is associated with arterial stiffness in men with newly diagnosed type 2 diabetes mellitus J. Zhang • G. Xiang • L. Xiang • H. Sun
Received: 16 March 2013 / Accepted: 17 November 2013 Ó Italian Society of Endocrinology (SIE) 2013
Abstract Background Increased serum uric acid levels and vascular atherosclerosis are very common in diabetes. However, few studies focused on the relationship between serum uric acid and aortic or peripheral arterial stiffness in newly diagnosed diabetic patients. This study investigated the association between serum uric acid levels and carotid– femoral pulse wave velocity (cfPWV) or carotid–radial (cr) PWV in male patients with newly diagnosed type 2 diabetes mellitus (T2DM). Methods 106 male patients with newly diagnosed T2DM were recruited. cfPWV and crPWV as well as anthropometric parameters, blood pressure, serum uric acid, blood glucose, fasting insulin, C-reactive protein and blood lipids were measured. Results The subjects were divided into low uric acid (UA) subgroup and high UA subgroup according to uric acid median. cfPWV and crPWV were significantly higher in high UA subgroup. Serum uric acid significantly correlated with cfPWV (r = 0.533, P \ 0.001), crPWV (r = 0.334, P = 0.001), waist circumference (r = 0.350, P \ 0.001), waist-to-hip ratio (r = 0.254, P = 0.009), fasting insulin (r = 0.432, P \ 0.001), HOMA-IR (r = 0.173, P = 0.042), fasting blood glucose (r = -0.271, P = 0.005), haemoglobin A1c (r = -0.202, P = 0.038), and HDL-cholesterol (r = -0.267, P = 0.006) after correction for age. Stepwise multiple regressions showed that the independent determinants of cfPWV were serum uric acid, age, C-reactive protein, HDL-cholesterol, and smoking status. And the independent
determinants of crPWV were serum uric acid, age, diastolic blood pressure, and HDL-cholesterol. Conclusions Serum uric acid is significantly associated with increased aortic and peripheral arterial stiffness in men with T2DM at the early stage.
J. Zhang (&) G. Xiang L. Xiang H. Sun Department of Endocrinology, Wuhan General Hospital of Guangzhou Command, Wuluo Road 627, Wuhan 430070, Hubei, People’s Republic of China e-mail: [email protected]
Introduction
Keywords Serum uric acid Pulse wave velocity Arterial stiffness Type 2 diabetes mellitus Abbreviations T2DM Type 2 diabetes mellitus CVD Cardiovascular disease cfPWV Carotid–femoral pulse wave velocity crPWV Carotid–radial pulse wave velocity IMT Intima-media thickness BMI Body mass index SBP Systolic blood pressure DBP Diastolic blood pressure LDL Low-density lipoprotein HDL High-density lipoprotein FBG Fasting blood glucose PBG Postprandial blood glucose HbA1c Haemoglobin A1c HOMA-IR Homeostasis model assessment index-insulin resistance UA Uric acid CRP C-reactive protein RAS Renin angiotensin system
Patients with type 2 diabetes mellitus (T2DM) are at a high risk of cardiovascular disease (CVD), which mainly
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contributes to the high morbidity and mortality of this population [1]. Arterial stiffness is known as an independent risk factor for cardiovascular disease. Pulse wave velocity (PWV), as a noninvasive method, is considered to be the ‘gold standard’ for the measurement of arterial stiffness, given its simplicity, accuracy, and reproducibility [2]. In general, carotid–femoral (cf) PWV has been used to measure aortic stiffness and carotid–radial (cr) PWV for the measurement of peripheral arterial stiffness [3]. Recent studies have suggested that increased peripheral and central arterial stiffness may partially explain why T2DM is associated with a high incidence of vasculopathy [4]. Several reports documented that uric acid plays a causal role in the development of metabolism syndrome, of which glucose intolerance is one of the main components [5, 6]. Increased serum uric acid levels are very common among diabetic patients even at the early stage, especially in men. Accumulating data have demonstrated that hyperuricemia is closely related to CVD [7, 8]. In line with this correlation, some studies have shown that serum uric acid is positively associated with carotid intima-media thickness (IMT) in T2DM [9]. And one study conducted in elderly people with T2DM indicated that uric acid levels show significant correlations with cfPWV [10]. However, no significant correlations were found between serum uric acid concentrations and brachial-ankle (ba) PWV in another study [11]. Hitherto, it remains unclear whether there are some differences in the association between serum uric acid levels and PWV measured from different sites. The purpose of this study was therefore to investigate whether serum uric acid levels are associated with PWV measured at two sites (cfPWV and crPWV) and whether this association is different in male patients with newly diagnosed T2DM. Relationships between cfPWV or crPWV and measured cardiovascular risk factors were also studied to clarify the influencing factors involved.
Materials and methods Subjects 304 consecutive male patients with newly diagnosed untreated T2DM were recruited in the study during 24-month period from January 2009 to December 2010. To avoid confounding factors, we excluded patients with hypertension, diabetic micro- and macro-vascular complications, malignant neoplasms, renal dysfunction or liver diseases, and urinary tract infection. Also, Patients were excluded if they were taking medications such as uric acidlowering agents or diuretics. Finally, 106 individuals were eligible for the present study. Ethical approval for the study
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was obtained from the local ethics committee and written informed consent forms were signed by each participant. Newly diagnosed T2DM was defined as either fasting glucose C7.0 mmol/L or post-challenge glucose C11.1 mmol/L or both on two occasions at least 48 h apart according to the 1999 WHO guidelines [12]. Patients with systolic blood pressure C140 mmHg and (or) diastolic blood pressure C90 mmHg were considered as hypertensives. Questionnaires to identify some details about lifestyle were sent to each participant. Those who had smoked at least one cigarette daily for 1 year were defined cigarette smokers. Alcohol consumption was defined as consuming alcohol more frequently than once a week. Family history was considered positive if a first-degree relative had been diagnosed as diabetes. Anthropometry and serum parameters Blood pressure, body height and weight were measured by the specially assigned nurses. Body mass index (BMI) was calculated as weight/height2 (kg/m2). After patients resting for 30 min, systolic and diastolic blood pressure (SBP and DBP) were measured using a mercury sphygmomanometer (Korotkoff phase I for systolic blood pressure and V for diastolic blood pressure). Venous blood samples were collected after an overnight fasting and immediately centrifuged. Serum uric acid, creatinine, total cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides and high-density lipoprotein (HDL) cholesterol concentrations were measured using standard enzymatic methods. Fasting blood glucose (FBG) and postprandial blood glucose (PBG) were measured by a glucose oxidase procedure. Haemoglobin A1c (HbA1c) was assayed using high-performance liquid chromatography. Fasting insulin was measured by radioimmunoassay. Insulin resistance was calculated using homeostasis model assessment index-insulin resistance (HOMA-IR). Ultrasensitive C-reactive protein (CRP) was measured by particle-enhanced immunoturbidimetric assay. Coefficients of variation for these assays were 1.0–2.0 % (uric acid, blood glucose, total cholesterol, HDL-cholesterol, HbA1c, creatinine) and 2–3 % (triglycerides, LDL-cholesterol, CRP, insulin), respectively. Pulse wave velocity Fasting and rested status was ensured for patients prior to PWV assessment. Subjects were supine while cfPWV and crPWV were measured noninvasively with the Complior Colson (Paris, France) device, as described previously [13]. Briefly, PWV along the artery was calculated using two strain-gauge transducers [TY-306 Fukuda pressure-sensitive transducer (Fukuda Denshi Company, Tokyo, Japan)]
J Endocrinol Invest
fixed transcutaneously over the course of a pair of arteries separated by a known distance: the right common carotid and femoral or radial arteries. During preprocessing analysis, the gain of each waveform was adjusted to obtain an equal signal for the two waveforms. During PWV measurements, when pulse waveforms of sufficient quality were recorded, the digitisation process was initiated by the operator and automatic calculation of the time delay between two upstrokes was started. Measurement was repeated over ten different cardiac cycles, and the mean value was used for the final analysis. PWV was automatically calculated as the ratio (m/s) of the distance travelled by the pulse wave to the time delay between the rapid upstrokes of the pulse waves simultaneously recorded. All the PWV measurements were performed by the same trained operator and the intra-operator coefficient of variation was about 2–6 %.
(UA) subgroup and high UA subgroup according to uric acid median. The differences between the two subgroups were compared by the Student’s independent-samples t test or Chi-square test in terms of the data distribution characteristics. Age-adjusted partial correlation analysis was performed to determine the association between serum uric acid levels and other several variables. Correlation coefficients between cf (cr) PWV and metabolic features were calculated by Pearson correlation analysis. A stepwise multiple regression analysis was performed to identify the independent association of serum uric acid with PWV. PWV was entered as the dependent variable, and all the variables associated with PWV in correlation analysis or ones which might affect PWV as independent variables. A P value \0.05 was considered statistically significant. All analyses were performed using SPSS statistical package (Version 17.0).
Statistical analysis Results Normality was tested using the Kolmogorov–Smirnov criterion. Non-normally distributed data were log transformed before analysis. Continuous variables are reported as mean ± standard deviation (SD). Categorical variables are expressed as numbers and percentages. All tests are two-tailed. The subjects were divided into low uric acid Table 1 Baseline characteristics of men with newly diagnosed T2DM according to uric acid median
Data are mean ± SD or percentage of participants HDL high-density lipoprotein, LDL low-density lipoprotein, HOMA-IR homeostasis model assessment index-insulin resistance, PWV pulse wave velocity
Characteristics
Clinical details and baseline characteristics of all the participants are illustrated in Table 1. We sub-divided the patients into low UA subgroup and high UA subgroup according to serum uric acid median (334 lmol/L). There was no significant difference in smoking ratio, alcohol Low UA (n = 53)
High UA (n = 53)
P value
Age (years)
45.9 ± 11.4
52.6 ± 9.7
0.002
Smoking [n (%)]
5 (9.43)
11 (20.76)
0.104
Alcohol [n (%)]
6 (11.32)
8 (15.09)
0.566
Family history of diabetes [n (%)]
8 (15.09)
6 (11.32)
0.566
Systolic blood pressure (mmHg)
125.3 ± 6.9
125.5 ± 9.2
0.915
Diastolic blood pressure (mmHg)
78.6 ± 4.9
78.5 ± 6.0
0.916
Body mass index (kg/m2)
25.20 ± 2.04
25.15 ± 2.24
0.909
Waist circumference (cm) Waist-to-hip ratio
86.94 ± 6.48 0.89 ± 0.05
89.87 ± 6.15 0.92 ± 0.04
0.019 0.017
Uric acid (lmol/L)
277.13 ± 47.77
372.68 ± 35.77
Creatinine (lmol/L)
71.80 ± 12.74
71.74 ± 13.15
C-reactive protein (mg/L)
1.21 ± 0.84
2.35 ± 0.79
\0.001 0.983 \0.001
Total cholesterol (mmol/L)
4.87 ± 1.32
4.94 ± 1.04
0.776
Triglycerides (mmol/L)
1.53 ± 1.09
1.57 ± 1.11
0.870
HDL-cholesterol (mmol/L)
1.27 ± 0.26
1.18 ± 0.24
0.087
LDL-cholesterol (mmol/L)
2.59 ± 0.89
2.53 ± 0.78
0.663
Fasting glucose (mmol/L)
8.81 ± 1.67
8.06 ± 1.31
0.011
Postprandial glucose (mmol/L)
14.13 ± 2.26
13.18 ± 2.11
0.028
Haemoglobin A1c (%)
8.82 ± 1.49
8.24 ± 1.34
Fasting insulin (mIU/L)
9.32 ± 1.46
11.99 ± 2.46
0.034 \0.001
HOMA-IR
3.66 ± 0.94
4.29 ± 1.08
\0.001
Carotid–femoral PWV (m/s)
10.35 ± 1.04
11.62 ± 0.96
\0.001
Carotid–radial PWV (m/s)
9.05 ± 0.95
9.75 ± 0.95
\0.001
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consumption ratio, positive family history ratio for diabetes, SBP, DBP, BMI, TC, TG, HDL-cholesterol as well as creatinine between the two groups. Compared with low UA
Table 2 Partial correlation analysis between serum uric acid concentration and other variables in men with T2DM Variables
Correlation coefficient
P value
Body mass index (kg/m2)
0.153
0.118
Waist circumference (cm)
0.350
\0.001
Waist-to-hip ratio
0.254
0.009
Fasting glucose (mmol/L)
-0.271
0.005
Haemoglobin A1C (%)a
-0.202
0.039
Fasting insulin (mIU/L)
0.432
\0.001
HOMA-IR
0.173
0.042
Creatinine (lmol/L)
0.188
0.055
C-reactive protein (mg/L)
0.507
\0.001
Systolic blood pressure (mmHg)
0.037
0.708
0.024 -0.033
0.811 0.741
Diastolic blood pressure (mmHg) Total cholesterol (mmol/L) Triglycerides (mmol/L)a
0.193
0.051
HDL-cholesterol (mmol/L)
-0.267
0.006
LDL-cholesterol (mmol/L)
-0.041
0.675
Carotid–femoral PWV (m/s)
0.533
\0.001
Carotid–radial PWV (m/s)
0.334
0.001
All correlation coefficients were calculated after correction for age using partial correlation analysis (n = 106) HDL high-density lipoprotein, LDL low-density lipoprotein, HOMAIR homeostasis model assessment index-insulin resistance, PWV pulse wave velocity a
Log-transformed values were used
Fig. 1 Correlation between serum uric acid levels and cfPWV or crPWV (a, b n = 106). The correlation coefficients were calculated after correction for age using partial correlation analysis (P \ 0.01).
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subgroup, patients with high uric acid levels exhibited higher age, waist circumference, waist-to-hip ratio, serum uric acid, CRP, fasting insulin, and HOMA-IR. Moreover, cfPWV and crPWV were significantly higher in high UA subgroup. However, levels of FBG, PBG, and HbA1c were relatively lower in patients with high uric acid. After correction for age, partial correlation analysis demonstrated that serum uric acid levels significantly correlated with cfPWV and crPWV (Table 2; Fig. 1). The linear regression equations could be mathematically expressed as Y (cfPWV) = 7.326 ? 0.011X (UA), Y (crPWV) = 7.151 ? 0.007X (UA), respectively. As shown in Table 2, serum uric acid levels also positively correlated with waist circumference, waist-to-hip ratio, fasting insulin, HOMA-IR, and CRP, but it negatively correlated with FBG, HbA1c, and HDL-cholesterol. Pearson correlation analysis demonstrated that cfPWV significantly correlated with age (r = 0.698, P \ 0.001), CRP (r = 0.637, P \ 0.001), FBG (r = -0.192, P = 0.049), HDL-cholesterol (r = -0.353, P \ 0.001), SBP (r = 0.416, P \ 0.001), smoking status (r = 0.512, P \ 0.001), fasting insulin (r = 0.372, P \ 0.001), and HOMA-IR (r = 0.225, P = 0.008), respectively. crPWV showed significant correlation with age (r = 0.444, P \ 0.001), CRP (r = 0.365, P \ 0.001), SBP (r = 0.315, P = 0.001), DBP (r = 0.395, P = 0.001), HDL-cholesterol (r = -0.352, P \ 0.001), triglycerides (r = 0.197, P = 0.043), fasting insulin (r = 0.216, P = 0.026), and HOMA-IR (r = 0.203, P = 0.037), respectively. Defining cfPWV as the dependent variable and all other factors, which are associated with cfPWV including age,
cfPWV carotid–femoral pulse wave velocity, crPWV carotid–radial pulse wave velocity
J Endocrinol Invest Table 3 Stepwise multiple regression analysis for the effect of independent variables on cfPWV or crPWV Variable
b
SE
t
P
cfPWV Age (years)
0.446
0.006
7.668 \0.001
C-reactive protein (mg/L)
0.219
0.082
3.193
Uric acid (lmol/L)
0.243
0.001
3.763 \0.001
Smoking status (yes) HDL-cholesterol (mmol/L) crPWV Age (years) Diastolic blood pressure (mmHg) Uric acid (lmol/L) HDL-cholesterol (mmol/L)
0.002
0.181
0.195
3.067
0.003
-0.141
0.251
-2.611
0.010 0.001
0.288
0.007
3.567
0.311
0.014
4.066 \0.001
0.258
0.001
3.093
0.003
-0.191
0.314
-2.414
0.018
Identifying the independent determinants of cfPWV and crPWV using the stepwise multiple regression models cfPWV carotid–femoral pulse wave velocity, crPWV carotid–radial pulse wave velocity, HDL high-density lipoprotein, LDL low-density lipoprotein
CRP, FBG, HDL-cholesterol, SBP, uric acid, fasting insulin, HOMA-IR, smoking status, and alcohol consumption, as the independent variables in a stepwise multiple regression model, the outcomes suggested that serum uric acid levels, age, CRP, smoking status and HDL-cholesterol levels were independent determinants of cfPWV (Table 3). While defining crPWV as the dependent variable and all other factors, which are associated with crPWV including age, CRP, SBP, DBP, HDL-cholesterol, uric acid, triglycerides, fasting insulin, HOMA-IR, smoking status, and alcohol consumption, as the independent variables, outcomes suggested that serum uric acid levels, age, DBP and HDL-cholesterol levels were the independent determinants of crPWV (Table 3).
Discussion In the present study, we found that serum uric acid levels strongly relate to cfPWV and crPWV in men with newly diagnosed T2DM, even after correction for other confounding factors. And the correlation is more pronounced for cfPWV. Serum uric acid levels are also found to be associated with other cardiovascular risk factors (CRP, FBP, HbA1c and HDL-C). In addition, of particular interest in our study was the finding that the dependent determinants of cfPW or crPWV are different. It is well known that increased serum uric acid and vascular atherosclerosis are very common in patients with diabetes. Although several studies have previously investigated the association between serum uric acid and PWV
in T2DM [10, 11], the population involved had a long duration in most cases, even including patients with diabetic micro- and macro-vascular complications, hypertensive, and those who were under medications which might affect serum uric acid levels. The results are controversial and it remains unclear whether the associations are different when PWV is measured from different sites. Hitherto, only few studies have focused on the association between serum uric acid and PWV in newly diagnosed diabetic patients. Our investigation here unveiled that serum uric acid levels are significantly related to PWV in diabetes, even after correction for other confounding factors. Moreover, our study demonstrates that the correlation is more pronounced for aortic arterial stiffening. And we reported here as the first that a linear association existed between serum uric acid levels and aortic PWV (cfPWV) or peripheral PWV (crPWV) in men with newly diagnosed T2DM. The possible mechanism which underlies the links between increased serum uric acid levels and arterial stiffness in patients with diabetes remains unclear. Several possible explanations should be concerned. Firstly, uric acid stimulates vascular smooth muscle cell (VSMC) proliferation and oxidative stress through vascular tissue renin angiotensin system (RAS) [14]. Secondly, uric acid causes dysfunction, ageing and death of human endothelial cells by decreasing the production of nitric oxide, activating oxidative stress, and up-regulating local tissue RAS expression [15, 16]. Thirdly, the link between uric acid and inflammatory activation in diverse settings also should be considered [9, 17–20]. Uric acid regulated critical proinflammatory pathways in rat vascular smooth muscle cells by increasing monocyte chemoattractant protein-1 (MCP1) expression [17]. Uric acid also has been shown to induce CRP expression in human vascular smooth muscle cells and human umbilical vein endothelial cells [18]. In human studies, serum uric acid levels were positively related to CRP in essential hypertension as well as type 2 diabetes mellitus [9, 19, 20], which is in agreement with our data. Lastly, uric acid may play a key role in promoting insulin resistance that in turn may affect vascular stiffness. Our data and several other studies suggested that serum uric acid levels were positively associated with insulin levels and homeostasis model assessment index [21, 22]. In another study, elevated serum uric acid levels were reported to be an independent predictor of hyperinsulinemia [23]. Moreover, a recent study showed that allopurinol significantly ameliorated insulin resistance of rats with hyperuricemia induced by high fructose diet [6]. These findings further indicate the role of uric acid involved in the development of increased arterial stiffness. In this study, we also observed the relationship between serum uric acid levels and several other
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parameters associated with CAD risk. Surprisingly, serum uric acid negatively related with glucose levels (FBG and HbA1c). This finding is in line with a recent report that serum uric acid shows inverse relationship with glucose levels in patients with type 2 diabetes [9]. It may be partially attributed to the hyperfiltration state caused by hyperglycemia promoting the excretion of uric acid. It is well documented that HDL-cholesterol has a protective effect on the cardiovascular system. As expected, we observed negative relationship between serum uric acid and HDL-cholesterol in the present study (r = -0.267, p = 0.006). Emerging evidences suggest that PWV increases in T2DM [11, 24–26]. However, it is possible that cardiovascular risk factors exert different effects on arterial stiffness of central elastic large artery and peripheral muscular medium-sized artery. According to multiple regression models, CRP and smoking status are found to only relate to cfPWV independently, which is in line with a study performed in Australia [27]. However, a stepwise multiple regression analysis demonstrated that DBP was only related to crPWV independently. This result confirms previous studies showing that DBP was associated with crPWV in coronary artery disease and essential hypertension [3, 28]. The difference in the independent determinants of aortic and peripheral stiffness may be attributed to different pathophysiological characteristics of central large artery and peripheral artery. It is well established that carotid–femoral arteries are more proximal, more elastic, less muscular, and with a larger diameter [29]. In this context, different arterial segments may respond differently to inflammatory factors, smoking and blood pressure [30]. However, the underlying mechanisms are not fully clear and deserve further research. This study has several limitations. Firstly, it is difficult to determine whether serum uric acid has a causative effect because of the cross-sectional design. Secondly, studies of larger subject number are urgently required to provide more definitive evidence. Thirdly, it is more meaningful if a longitudinal study will be taken to investigate the incidence of vascular events or mortality in diabetic patients with hyperuricemia. Lastly, it is uncertain whether these results are generalizable in females because only males were recruited in our study. Despite the limitations mentioned above, our investigation demonstrates that uric acid may play a role in the development and progression of arteriosclerosis in diabetic patients even in the initial period. This provides important information for understanding the mechanisms of increased arterial stiffness related to diabetic patients with higher serum uric acid. Our findings imply that serum uric acid may become one of the early prevention targets for the patients under these circumstances.
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In conclusion, our data demonstrate that serum uric acid is significantly associated with increased aortic and peripheral arterial stiffness in men with T2DM at the early stage, even after correction for other confounding factors. Prospective studies are urgently needed to determine the causal relationships between serum uric acid levels and the development of atherosclerosis in T2DM. Conflict of interest The authors Junxia Zhang, Guangda Xiang, Lin Xiang, and Huiling Sun declare that they have no conflict of interest.
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ORIGINAL ARTICLE
Serum uric acid is associated with arterial stiffness in men with newly diagnosed type 2 diabetes mellitus J. Zhang • G. Xiang • L. Xiang • H. Sun
Received: 16 March 2013 / Accepted: 17 November 2013 Ó Italian Society of Endocrinology (SIE) 2013
Abstract Background Increased serum uric acid levels and vascular atherosclerosis are very common in diabetes. However, few studies focused on the relationship between serum uric acid and aortic or peripheral arterial stiffness in newly diagnosed diabetic patients. This study investigated the association between serum uric acid levels and carotid– femoral pulse wave velocity (cfPWV) or carotid–radial (cr) PWV in male patients with newly diagnosed type 2 diabetes mellitus (T2DM). Methods 106 male patients with newly diagnosed T2DM were recruited. cfPWV and crPWV as well as anthropometric parameters, blood pressure, serum uric acid, blood glucose, fasting insulin, C-reactive protein and blood lipids were measured. Results The subjects were divided into low uric acid (UA) subgroup and high UA subgroup according to uric acid median. cfPWV and crPWV were significantly higher in high UA subgroup. Serum uric acid significantly correlated with cfPWV (r = 0.533, P \ 0.001), crPWV (r = 0.334, P = 0.001), waist circumference (r = 0.350, P \ 0.001), waist-to-hip ratio (r = 0.254, P = 0.009), fasting insulin (r = 0.432, P \ 0.001), HOMA-IR (r = 0.173, P = 0.042), fasting blood glucose (r = -0.271, P = 0.005), haemoglobin A1c (r = -0.202, P = 0.038), and HDL-cholesterol (r = -0.267, P = 0.006) after correction for age. Stepwise multiple regressions showed that the independent determinants of cfPWV were serum uric acid, age, C-reactive protein, HDL-cholesterol, and smoking status. And the independent
determinants of crPWV were serum uric acid, age, diastolic blood pressure, and HDL-cholesterol. Conclusions Serum uric acid is significantly associated with increased aortic and peripheral arterial stiffness in men with T2DM at the early stage.
J. Zhang (&) G. Xiang L. Xiang H. Sun Department of Endocrinology, Wuhan General Hospital of Guangzhou Command, Wuluo Road 627, Wuhan 430070, Hubei, People’s Republic of China e-mail: [email protected]
Introduction
Keywords Serum uric acid Pulse wave velocity Arterial stiffness Type 2 diabetes mellitus Abbreviations T2DM Type 2 diabetes mellitus CVD Cardiovascular disease cfPWV Carotid–femoral pulse wave velocity crPWV Carotid–radial pulse wave velocity IMT Intima-media thickness BMI Body mass index SBP Systolic blood pressure DBP Diastolic blood pressure LDL Low-density lipoprotein HDL High-density lipoprotein FBG Fasting blood glucose PBG Postprandial blood glucose HbA1c Haemoglobin A1c HOMA-IR Homeostasis model assessment index-insulin resistance UA Uric acid CRP C-reactive protein RAS Renin angiotensin system
Patients with type 2 diabetes mellitus (T2DM) are at a high risk of cardiovascular disease (CVD), which mainly
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contributes to the high morbidity and mortality of this population [1]. Arterial stiffness is known as an independent risk factor for cardiovascular disease. Pulse wave velocity (PWV), as a noninvasive method, is considered to be the ‘gold standard’ for the measurement of arterial stiffness, given its simplicity, accuracy, and reproducibility [2]. In general, carotid–femoral (cf) PWV has been used to measure aortic stiffness and carotid–radial (cr) PWV for the measurement of peripheral arterial stiffness [3]. Recent studies have suggested that increased peripheral and central arterial stiffness may partially explain why T2DM is associated with a high incidence of vasculopathy [4]. Several reports documented that uric acid plays a causal role in the development of metabolism syndrome, of which glucose intolerance is one of the main components [5, 6]. Increased serum uric acid levels are very common among diabetic patients even at the early stage, especially in men. Accumulating data have demonstrated that hyperuricemia is closely related to CVD [7, 8]. In line with this correlation, some studies have shown that serum uric acid is positively associated with carotid intima-media thickness (IMT) in T2DM [9]. And one study conducted in elderly people with T2DM indicated that uric acid levels show significant correlations with cfPWV [10]. However, no significant correlations were found between serum uric acid concentrations and brachial-ankle (ba) PWV in another study [11]. Hitherto, it remains unclear whether there are some differences in the association between serum uric acid levels and PWV measured from different sites. The purpose of this study was therefore to investigate whether serum uric acid levels are associated with PWV measured at two sites (cfPWV and crPWV) and whether this association is different in male patients with newly diagnosed T2DM. Relationships between cfPWV or crPWV and measured cardiovascular risk factors were also studied to clarify the influencing factors involved.
Materials and methods Subjects 304 consecutive male patients with newly diagnosed untreated T2DM were recruited in the study during 24-month period from January 2009 to December 2010. To avoid confounding factors, we excluded patients with hypertension, diabetic micro- and macro-vascular complications, malignant neoplasms, renal dysfunction or liver diseases, and urinary tract infection. Also, Patients were excluded if they were taking medications such as uric acidlowering agents or diuretics. Finally, 106 individuals were eligible for the present study. Ethical approval for the study
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was obtained from the local ethics committee and written informed consent forms were signed by each participant. Newly diagnosed T2DM was defined as either fasting glucose C7.0 mmol/L or post-challenge glucose C11.1 mmol/L or both on two occasions at least 48 h apart according to the 1999 WHO guidelines [12]. Patients with systolic blood pressure C140 mmHg and (or) diastolic blood pressure C90 mmHg were considered as hypertensives. Questionnaires to identify some details about lifestyle were sent to each participant. Those who had smoked at least one cigarette daily for 1 year were defined cigarette smokers. Alcohol consumption was defined as consuming alcohol more frequently than once a week. Family history was considered positive if a first-degree relative had been diagnosed as diabetes. Anthropometry and serum parameters Blood pressure, body height and weight were measured by the specially assigned nurses. Body mass index (BMI) was calculated as weight/height2 (kg/m2). After patients resting for 30 min, systolic and diastolic blood pressure (SBP and DBP) were measured using a mercury sphygmomanometer (Korotkoff phase I for systolic blood pressure and V for diastolic blood pressure). Venous blood samples were collected after an overnight fasting and immediately centrifuged. Serum uric acid, creatinine, total cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides and high-density lipoprotein (HDL) cholesterol concentrations were measured using standard enzymatic methods. Fasting blood glucose (FBG) and postprandial blood glucose (PBG) were measured by a glucose oxidase procedure. Haemoglobin A1c (HbA1c) was assayed using high-performance liquid chromatography. Fasting insulin was measured by radioimmunoassay. Insulin resistance was calculated using homeostasis model assessment index-insulin resistance (HOMA-IR). Ultrasensitive C-reactive protein (CRP) was measured by particle-enhanced immunoturbidimetric assay. Coefficients of variation for these assays were 1.0–2.0 % (uric acid, blood glucose, total cholesterol, HDL-cholesterol, HbA1c, creatinine) and 2–3 % (triglycerides, LDL-cholesterol, CRP, insulin), respectively. Pulse wave velocity Fasting and rested status was ensured for patients prior to PWV assessment. Subjects were supine while cfPWV and crPWV were measured noninvasively with the Complior Colson (Paris, France) device, as described previously [13]. Briefly, PWV along the artery was calculated using two strain-gauge transducers [TY-306 Fukuda pressure-sensitive transducer (Fukuda Denshi Company, Tokyo, Japan)]
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fixed transcutaneously over the course of a pair of arteries separated by a known distance: the right common carotid and femoral or radial arteries. During preprocessing analysis, the gain of each waveform was adjusted to obtain an equal signal for the two waveforms. During PWV measurements, when pulse waveforms of sufficient quality were recorded, the digitisation process was initiated by the operator and automatic calculation of the time delay between two upstrokes was started. Measurement was repeated over ten different cardiac cycles, and the mean value was used for the final analysis. PWV was automatically calculated as the ratio (m/s) of the distance travelled by the pulse wave to the time delay between the rapid upstrokes of the pulse waves simultaneously recorded. All the PWV measurements were performed by the same trained operator and the intra-operator coefficient of variation was about 2–6 %.
(UA) subgroup and high UA subgroup according to uric acid median. The differences between the two subgroups were compared by the Student’s independent-samples t test or Chi-square test in terms of the data distribution characteristics. Age-adjusted partial correlation analysis was performed to determine the association between serum uric acid levels and other several variables. Correlation coefficients between cf (cr) PWV and metabolic features were calculated by Pearson correlation analysis. A stepwise multiple regression analysis was performed to identify the independent association of serum uric acid with PWV. PWV was entered as the dependent variable, and all the variables associated with PWV in correlation analysis or ones which might affect PWV as independent variables. A P value \0.05 was considered statistically significant. All analyses were performed using SPSS statistical package (Version 17.0).
Statistical analysis Results Normality was tested using the Kolmogorov–Smirnov criterion. Non-normally distributed data were log transformed before analysis. Continuous variables are reported as mean ± standard deviation (SD). Categorical variables are expressed as numbers and percentages. All tests are two-tailed. The subjects were divided into low uric acid Table 1 Baseline characteristics of men with newly diagnosed T2DM according to uric acid median
Data are mean ± SD or percentage of participants HDL high-density lipoprotein, LDL low-density lipoprotein, HOMA-IR homeostasis model assessment index-insulin resistance, PWV pulse wave velocity
Characteristics
Clinical details and baseline characteristics of all the participants are illustrated in Table 1. We sub-divided the patients into low UA subgroup and high UA subgroup according to serum uric acid median (334 lmol/L). There was no significant difference in smoking ratio, alcohol Low UA (n = 53)
High UA (n = 53)
P value
Age (years)
45.9 ± 11.4
52.6 ± 9.7
0.002
Smoking [n (%)]
5 (9.43)
11 (20.76)
0.104
Alcohol [n (%)]
6 (11.32)
8 (15.09)
0.566
Family history of diabetes [n (%)]
8 (15.09)
6 (11.32)
0.566
Systolic blood pressure (mmHg)
125.3 ± 6.9
125.5 ± 9.2
0.915
Diastolic blood pressure (mmHg)
78.6 ± 4.9
78.5 ± 6.0
0.916
Body mass index (kg/m2)
25.20 ± 2.04
25.15 ± 2.24
0.909
Waist circumference (cm) Waist-to-hip ratio
86.94 ± 6.48 0.89 ± 0.05
89.87 ± 6.15 0.92 ± 0.04
0.019 0.017
Uric acid (lmol/L)
277.13 ± 47.77
372.68 ± 35.77
Creatinine (lmol/L)
71.80 ± 12.74
71.74 ± 13.15
C-reactive protein (mg/L)
1.21 ± 0.84
2.35 ± 0.79
\0.001 0.983 \0.001
Total cholesterol (mmol/L)
4.87 ± 1.32
4.94 ± 1.04
0.776
Triglycerides (mmol/L)
1.53 ± 1.09
1.57 ± 1.11
0.870
HDL-cholesterol (mmol/L)
1.27 ± 0.26
1.18 ± 0.24
0.087
LDL-cholesterol (mmol/L)
2.59 ± 0.89
2.53 ± 0.78
0.663
Fasting glucose (mmol/L)
8.81 ± 1.67
8.06 ± 1.31
0.011
Postprandial glucose (mmol/L)
14.13 ± 2.26
13.18 ± 2.11
0.028
Haemoglobin A1c (%)
8.82 ± 1.49
8.24 ± 1.34
Fasting insulin (mIU/L)
9.32 ± 1.46
11.99 ± 2.46
0.034 \0.001
HOMA-IR
3.66 ± 0.94
4.29 ± 1.08
\0.001
Carotid–femoral PWV (m/s)
10.35 ± 1.04
11.62 ± 0.96
\0.001
Carotid–radial PWV (m/s)
9.05 ± 0.95
9.75 ± 0.95
\0.001
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consumption ratio, positive family history ratio for diabetes, SBP, DBP, BMI, TC, TG, HDL-cholesterol as well as creatinine between the two groups. Compared with low UA
Table 2 Partial correlation analysis between serum uric acid concentration and other variables in men with T2DM Variables
Correlation coefficient
P value
Body mass index (kg/m2)
0.153
0.118
Waist circumference (cm)
0.350
\0.001
Waist-to-hip ratio
0.254
0.009
Fasting glucose (mmol/L)
-0.271
0.005
Haemoglobin A1C (%)a
-0.202
0.039
Fasting insulin (mIU/L)
0.432
\0.001
HOMA-IR
0.173
0.042
Creatinine (lmol/L)
0.188
0.055
C-reactive protein (mg/L)
0.507
\0.001
Systolic blood pressure (mmHg)
0.037
0.708
0.024 -0.033
0.811 0.741
Diastolic blood pressure (mmHg) Total cholesterol (mmol/L) Triglycerides (mmol/L)a
0.193
0.051
HDL-cholesterol (mmol/L)
-0.267
0.006
LDL-cholesterol (mmol/L)
-0.041
0.675
Carotid–femoral PWV (m/s)
0.533
\0.001
Carotid–radial PWV (m/s)
0.334
0.001
All correlation coefficients were calculated after correction for age using partial correlation analysis (n = 106) HDL high-density lipoprotein, LDL low-density lipoprotein, HOMAIR homeostasis model assessment index-insulin resistance, PWV pulse wave velocity a
Log-transformed values were used
Fig. 1 Correlation between serum uric acid levels and cfPWV or crPWV (a, b n = 106). The correlation coefficients were calculated after correction for age using partial correlation analysis (P \ 0.01).
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subgroup, patients with high uric acid levels exhibited higher age, waist circumference, waist-to-hip ratio, serum uric acid, CRP, fasting insulin, and HOMA-IR. Moreover, cfPWV and crPWV were significantly higher in high UA subgroup. However, levels of FBG, PBG, and HbA1c were relatively lower in patients with high uric acid. After correction for age, partial correlation analysis demonstrated that serum uric acid levels significantly correlated with cfPWV and crPWV (Table 2; Fig. 1). The linear regression equations could be mathematically expressed as Y (cfPWV) = 7.326 ? 0.011X (UA), Y (crPWV) = 7.151 ? 0.007X (UA), respectively. As shown in Table 2, serum uric acid levels also positively correlated with waist circumference, waist-to-hip ratio, fasting insulin, HOMA-IR, and CRP, but it negatively correlated with FBG, HbA1c, and HDL-cholesterol. Pearson correlation analysis demonstrated that cfPWV significantly correlated with age (r = 0.698, P \ 0.001), CRP (r = 0.637, P \ 0.001), FBG (r = -0.192, P = 0.049), HDL-cholesterol (r = -0.353, P \ 0.001), SBP (r = 0.416, P \ 0.001), smoking status (r = 0.512, P \ 0.001), fasting insulin (r = 0.372, P \ 0.001), and HOMA-IR (r = 0.225, P = 0.008), respectively. crPWV showed significant correlation with age (r = 0.444, P \ 0.001), CRP (r = 0.365, P \ 0.001), SBP (r = 0.315, P = 0.001), DBP (r = 0.395, P = 0.001), HDL-cholesterol (r = -0.352, P \ 0.001), triglycerides (r = 0.197, P = 0.043), fasting insulin (r = 0.216, P = 0.026), and HOMA-IR (r = 0.203, P = 0.037), respectively. Defining cfPWV as the dependent variable and all other factors, which are associated with cfPWV including age,
cfPWV carotid–femoral pulse wave velocity, crPWV carotid–radial pulse wave velocity
J Endocrinol Invest Table 3 Stepwise multiple regression analysis for the effect of independent variables on cfPWV or crPWV Variable
b
SE
t
P
cfPWV Age (years)
0.446
0.006
7.668 \0.001
C-reactive protein (mg/L)
0.219
0.082
3.193
Uric acid (lmol/L)
0.243
0.001
3.763 \0.001
Smoking status (yes) HDL-cholesterol (mmol/L) crPWV Age (years) Diastolic blood pressure (mmHg) Uric acid (lmol/L) HDL-cholesterol (mmol/L)
0.002
0.181
0.195
3.067
0.003
-0.141
0.251
-2.611
0.010 0.001
0.288
0.007
3.567
0.311
0.014
4.066 \0.001
0.258
0.001
3.093
0.003
-0.191
0.314
-2.414
0.018
Identifying the independent determinants of cfPWV and crPWV using the stepwise multiple regression models cfPWV carotid–femoral pulse wave velocity, crPWV carotid–radial pulse wave velocity, HDL high-density lipoprotein, LDL low-density lipoprotein
CRP, FBG, HDL-cholesterol, SBP, uric acid, fasting insulin, HOMA-IR, smoking status, and alcohol consumption, as the independent variables in a stepwise multiple regression model, the outcomes suggested that serum uric acid levels, age, CRP, smoking status and HDL-cholesterol levels were independent determinants of cfPWV (Table 3). While defining crPWV as the dependent variable and all other factors, which are associated with crPWV including age, CRP, SBP, DBP, HDL-cholesterol, uric acid, triglycerides, fasting insulin, HOMA-IR, smoking status, and alcohol consumption, as the independent variables, outcomes suggested that serum uric acid levels, age, DBP and HDL-cholesterol levels were the independent determinants of crPWV (Table 3).
Discussion In the present study, we found that serum uric acid levels strongly relate to cfPWV and crPWV in men with newly diagnosed T2DM, even after correction for other confounding factors. And the correlation is more pronounced for cfPWV. Serum uric acid levels are also found to be associated with other cardiovascular risk factors (CRP, FBP, HbA1c and HDL-C). In addition, of particular interest in our study was the finding that the dependent determinants of cfPW or crPWV are different. It is well known that increased serum uric acid and vascular atherosclerosis are very common in patients with diabetes. Although several studies have previously investigated the association between serum uric acid and PWV
in T2DM [10, 11], the population involved had a long duration in most cases, even including patients with diabetic micro- and macro-vascular complications, hypertensive, and those who were under medications which might affect serum uric acid levels. The results are controversial and it remains unclear whether the associations are different when PWV is measured from different sites. Hitherto, only few studies have focused on the association between serum uric acid and PWV in newly diagnosed diabetic patients. Our investigation here unveiled that serum uric acid levels are significantly related to PWV in diabetes, even after correction for other confounding factors. Moreover, our study demonstrates that the correlation is more pronounced for aortic arterial stiffening. And we reported here as the first that a linear association existed between serum uric acid levels and aortic PWV (cfPWV) or peripheral PWV (crPWV) in men with newly diagnosed T2DM. The possible mechanism which underlies the links between increased serum uric acid levels and arterial stiffness in patients with diabetes remains unclear. Several possible explanations should be concerned. Firstly, uric acid stimulates vascular smooth muscle cell (VSMC) proliferation and oxidative stress through vascular tissue renin angiotensin system (RAS) [14]. Secondly, uric acid causes dysfunction, ageing and death of human endothelial cells by decreasing the production of nitric oxide, activating oxidative stress, and up-regulating local tissue RAS expression [15, 16]. Thirdly, the link between uric acid and inflammatory activation in diverse settings also should be considered [9, 17–20]. Uric acid regulated critical proinflammatory pathways in rat vascular smooth muscle cells by increasing monocyte chemoattractant protein-1 (MCP1) expression [17]. Uric acid also has been shown to induce CRP expression in human vascular smooth muscle cells and human umbilical vein endothelial cells [18]. In human studies, serum uric acid levels were positively related to CRP in essential hypertension as well as type 2 diabetes mellitus [9, 19, 20], which is in agreement with our data. Lastly, uric acid may play a key role in promoting insulin resistance that in turn may affect vascular stiffness. Our data and several other studies suggested that serum uric acid levels were positively associated with insulin levels and homeostasis model assessment index [21, 22]. In another study, elevated serum uric acid levels were reported to be an independent predictor of hyperinsulinemia [23]. Moreover, a recent study showed that allopurinol significantly ameliorated insulin resistance of rats with hyperuricemia induced by high fructose diet [6]. These findings further indicate the role of uric acid involved in the development of increased arterial stiffness. In this study, we also observed the relationship between serum uric acid levels and several other
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parameters associated with CAD risk. Surprisingly, serum uric acid negatively related with glucose levels (FBG and HbA1c). This finding is in line with a recent report that serum uric acid shows inverse relationship with glucose levels in patients with type 2 diabetes [9]. It may be partially attributed to the hyperfiltration state caused by hyperglycemia promoting the excretion of uric acid. It is well documented that HDL-cholesterol has a protective effect on the cardiovascular system. As expected, we observed negative relationship between serum uric acid and HDL-cholesterol in the present study (r = -0.267, p = 0.006). Emerging evidences suggest that PWV increases in T2DM [11, 24–26]. However, it is possible that cardiovascular risk factors exert different effects on arterial stiffness of central elastic large artery and peripheral muscular medium-sized artery. According to multiple regression models, CRP and smoking status are found to only relate to cfPWV independently, which is in line with a study performed in Australia [27]. However, a stepwise multiple regression analysis demonstrated that DBP was only related to crPWV independently. This result confirms previous studies showing that DBP was associated with crPWV in coronary artery disease and essential hypertension [3, 28]. The difference in the independent determinants of aortic and peripheral stiffness may be attributed to different pathophysiological characteristics of central large artery and peripheral artery. It is well established that carotid–femoral arteries are more proximal, more elastic, less muscular, and with a larger diameter [29]. In this context, different arterial segments may respond differently to inflammatory factors, smoking and blood pressure [30]. However, the underlying mechanisms are not fully clear and deserve further research. This study has several limitations. Firstly, it is difficult to determine whether serum uric acid has a causative effect because of the cross-sectional design. Secondly, studies of larger subject number are urgently required to provide more definitive evidence. Thirdly, it is more meaningful if a longitudinal study will be taken to investigate the incidence of vascular events or mortality in diabetic patients with hyperuricemia. Lastly, it is uncertain whether these results are generalizable in females because only males were recruited in our study. Despite the limitations mentioned above, our investigation demonstrates that uric acid may play a role in the development and progression of arteriosclerosis in diabetic patients even in the initial period. This provides important information for understanding the mechanisms of increased arterial stiffness related to diabetic patients with higher serum uric acid. Our findings imply that serum uric acid may become one of the early prevention targets for the patients under these circumstances.
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In conclusion, our data demonstrate that serum uric acid is significantly associated with increased aortic and peripheral arterial stiffness in men with T2DM at the early stage, even after correction for other confounding factors. Prospective studies are urgently needed to determine the causal relationships between serum uric acid levels and the development of atherosclerosis in T2DM. Conflict of interest The authors Junxia Zhang, Guangda Xiang, Lin Xiang, and Huiling Sun declare that they have no conflict of interest.
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