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Subclinical carotid atherosclerosis and hyperuricemia in relation to renal impairment in a rural Japanese population: The Nagasaki Islands study
Atherosclerosis 233 (2014) 525e529
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Subclinical carotid atherosclerosis and hyperuricemia in relation to renal impairment in a rural Japanese population: The Nagasaki Islands study Yuji Shimizu a, *, Shimpei Sato a, Jun Koyamatsu b, Hirotomo Yamanashi b, Mami Tamai c, Koichiro Kadota a, Kazuhiko Arima d, Hironori Yamasaki e, Noboru Takamura f, Kiyoshi Aoyagi d, Takahiro Maeda a, b a
Department of Community Medicine, Nagasaki University Graduate School of Biomedical Science, Nagasaki, Japan Department of Island and Community Medicine, Nagasaki University Graduate School of Biomedical Science, Nagasaki, Japan c Unit of Translational Medicine, Department of Immunology and Rheumatology, Nagasaki University Graduate School of Biomedical Science, Nagasaki, Japan d Department of Public Health, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan e Center for Health and Community Medicine, Nagasaki University, Nagasaki, Japan f Department of Global Health, Medicine and Welfare, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 24 October 2013 Received in revised form 15 January 2014 Accepted 15 January 2014 Available online 27 January 2014
Objective: The influence of hyperuricemia on atherosclerosis is controversial. Subclinical carotid atherosclerosis can be defined in two ways in terms of mean and maximum carotid intima-media thickness (CIMT): one with mean CIMT 1.1 mm and the other with maximum CIMT 1.1 mm. However, no studies have been reported of the association between hyperuricemia and subclinical carotid atherosclerosis while taking the two different ways of classification into account. Methods: We conducted a cross-sectional study of 4133 subjects (1492 men and 2641 women) aged 30 e89 years undergoing general health check-ups. For analysis of various associations, we calculated the multivariable odds ratios (ORs) for the two ways classifications of subclinical carotid atherosclerosis in relation to hyperuricemia. Results: Hyperuricemia-related renal impairment constitutes a significant marker for subclinical carotid atherosclerosis with mean CIMT 1.1 mm for both men and women, while hyperuricemia per se was found to be beneficially associated with risk of subclinical carotid atherosclerosis with maximum CIMT 1.1 mm for men. The classical cardiovascular risk factors without adjustment for glomerular filtration rate (GFR) of ORs for subclinical carotid atherosclerosis (mean CIMT 1.1 mm) and subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) were 2.20(1.10e4.22) and 0.84(0.63e1.13) for men and 2.12(1.02e4.38) and 0.92(0.66e1.27) for women. After further adjustment for GFR, the corresponding values were 1.54(0.74e3.20) and 0.67(0.49e0.92) for men and 1.32(0.61e2.88) and 0.80(0.57 e1.12) for women. Conclusion: Hyperuricemia-related renal impairment is a significant marker for subclinical carotid atherosclerosis for both men and women, while hyperuricemia per se may be inversely associated with subclinical carotid atherosclerosis for men as seen in a rural community-dwelling Japanese population. Ó 2014 Elsevier Ireland Ltd. All rights reserved.
Keywords: CIMT Hyperuricemia Cross-sectional study
1. Introduction The influence of hyperuricemia on atherosclerosis remains a matter of debate. A previous sex-combined study with 181 participants who underwent transesophageal echocardiography reported that uric acid is independently and positively associated with subclinical thoracic atherosclerosis [1]. However, the * Corresponding author. E-mail address: [email protected] (Y. Shimizu). 0021-9150/$ e see front matter Ó 2014 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atherosclerosis.2014.01.033
Atherosclerosis Risk in Communities Study (ARIC Study) reported that uric acid per se may not be a risk factor for atherosclerosis [2]. In fact, another study hypothesized that uric acid generates an antioxidant defense in humans, so that it might offer protection against oxidative stress in atherosclerosis [3,4]. On the other hand, hyperuricemia is a well-known factor that is positively associated with various forms of renal impairment such as chronic kidney disease (CKD) [5,6] while renal impairment is also known to be associated with atherosclerosis [7,8] and stroke [9]. The beneficial effect on atherosclerosis might therefore be masked by a condition
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underlying hyperuricemia, which is associated with both hyperuricemia and atherosclerosis. This implies that a background of hyperuricemia, like renal impairment, may therefore often be associated with a systemically higher risk of atherosclerosis even though hyperuricemia per se has a protective effect on progression of minor atherosclerosis. While subclinical carotid atherosclerosis with mean CIMT 1.1 mm systemically indicates carotid atherosclerosis, subclinical carotid atherosclerosis with maximum CIMT 1.1 mm may have a strong effect on minor atherosclerosis. We hypothesized that hyperuricemia constitutes a marker of subclinical carotid atherosclerosis with mean CIMT 1.1 mm but has a beneficial effect on subclinical carotid atherosclerosis with maximum CIMT 1.1 mm and that these associations are strongly influenced by the renal condition. To investigate these associations, we performed a cross-sectional study of subjects undergoing general health check-ups. 2. Subjects and methods This study was approved by the Ethics Committee for Use of Humans of Nagasaki University (project registration number 0501120073). The survey population comprised 4269 participants (1538 men and 2731 women) aged 30e89 years, all residents of the western rural community of the Goto Islands, who participated in this study between 2005 and 2012. A total of 136 individuals (46 men and 90 women) with missing data were excluded, leaving 4133 participants (1492 men and 2641 women) for enrollment in this study. The mean age of the study population was 65.5 years (10.7 SD; range 30e89) for men and 63.9 years (11.4 SD; range 30e89) for women. Systolic and diastolic blood pressures at rest were recorded with a blood pressure measuring device (HEM-907; Omron, Kyoto, Japan). Body weight and height were measured with an automatic body composition analyzer (BF-220; Tanita, Tokyo, Japan) at the time of drawing blood. Fasting blood samples were obtained and the serum was separated and centrifuged after blood coagulation. Serum triglycerides, serum HDL-cholesterol, serum aspartate aminotransferase (AST), serum g-glutamyltranspeptidase (gGTP), serum creatinine, and HbA1c were measured with standard laboratory procedures. Trained interviewers obtained information on smoking status, drinking status, medical history, use of antihypertensive agents and of medication for diabetes mellitus. The glomerular filtration rate (GFR) was estimated with an established method with three variations recently proposed by a working group of the Japanese Chronic Kidney Disease Initiative [10]. According to this adaptation, GFR (mL/min/1.73 m2) ¼ 194 (serum creatinine (enzyme method))1.094 (age)0.287 (0.739 for women). CKD was defined as GFR <60 mL/min per 1.73 m2 in accordance with the National Kidney Disease Outcomes Quality Initiative guidelines [11]. HbA1c (as defined by NGSP, the National Glycohemoglobin Standardization Program) was calculated with the following equation, which was recently proposed by a working group of the Japanese Diabetes Society: (JDS): HbA1c(NGSP) ¼ HbA1c(JDS) þ 0.4%. Presence of diabetes was defined as HbA1c (NGSP) 6.5%, and/or initiation of glucose-lowering medication or insulin therapy [12]. Hyperuricemia was defined as a serum uric acid level >7 mg/dL. 2.1. Carotid B-mode ultrasound imaging Measurement of CIMT by ultrasonography of the left and right carotid arteries was performed by two medical doctors (N.T. and M.N.) using a LOGIQ Book XP with a 10-MHz transducer (GE Healthcare, Milwaukee, WI, USA) that was programmed with the IMT measurement software Intimascope (Cross Media Ltd., Tokyo,
Japan) [13]. The protocol used has been described in detail elsewhere [14]. Mean CIMT was calculated as the mean of right and left CIMT measurements with carotid plaques excluded, and maximum CIMT was defined as the highest CIMT measurement on either side. Since a previous study reported the normal CIMT value was <1.1 mm [15] and that of elevated CIMT value 1.1 mm [16], while a previous study of ours produced a definition of atherosclerosis as maximum CIMT 1.1 mm [17], we classified subclinical carotid atherosclerosis in two ways; subclinical carotid atherosclerosis with mean CIMT 1.1 mm and subclinical carotid atherosclerosis with maximum CIMT 1.1 mm. Intra-observer variation agreement for CIMT (N.T., n ¼ 32) was 0.91 (p < 0.01), and interobserver variation agreement (N.T. vs. M.N., n ¼ 41) was 0.78 (p < 0.01). 2.2. Statistical analysis Differences in age-adjusted mean values or prevalence of potential confounding factors according to CKD category and hyperuricemia category were analyzed by using covariance or general linear models, and logistic regression models were used for calculating odds ratios (ORs) and 95% confidence intervals (CIs) for associations with subclinical carotid atherosclerosis. Three different approaches were used for making adjustments for confounding factors. First, the data were adjusted only for age (Model 1). Second, we included other possible confounding factors, namely smoking status (never smoker, former smoker, current smoker), alcohol intake [non-drinker, current light to moderate drinker (1e6 times/week), current heavy drinker (every day)], systolic blood pressure (mmHg), antihypertensive medication use (no, yes), history of cardiovascular disease (no, yes), diabetes (no, yes), body mass index (kg/m2), serum triglyceride (mg/dL), serum HDL-cholesterol (mg/dL), AST (IU/L), and g-GTP (IU/L) (Model 2). Third, we made further adjustments for GFR (Model 3). All statistical analyses were performed with the SAS system for Windows (version 9.3; SAS Inc., Cary, NC). All p-values for statistical tests were two-tailed, and values of <0.05 were regarded as statistically significant. 3. Results 3.1. Characteristics of the study population Table 1 shows sex-specific characteristics of the study population by CKD and hyperuricemia status. Of the 1492 men and 2641 women, 398 and 855, respectively, were diagnosed with CKD, and the corresponding number for diagnosis of hyperuricemia were 411 and 317. Overall, both male and female participants with CKD or hyperuricemia proved to have higher cardiovascular risk factors than those without either of these abnormalities. 3.2. Association between subclinical carotid atherosclerosis and CKD Table 2 shows the association between subclinical carotid atherosclerosis and CKD. Regardless of classical cardiovascular risk factors, CKD constitutes a significant risk for subclinical carotid atherosclerosis with mean CIMT 1.1 mm for both men and women, but after further adjustment for GFR, this association no longer held. Essentially the same association was observed for subclinical carotid atherosclerosis with maximum CIMT 1.1 mm.
Y. Shimizu et al. / Atherosclerosis 233 (2014) 525e529
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Table 1 Sex-specific clinical characteristics of the study population with chronic kidney disease (CKD) and hyperuricemia. Hyperuricemia
Men Target persons, n Age Serum uric acid, mg/dL Carotid intima-media thickness (mean CIMT), mm Subclinical carotid atherosclerosis (mean CIMT 1.1 mm), % Carotid intima-media thickness (maximum CIMT), mm Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm), % Body mass index, kg/m2 Systolic blood pressure, mmHg Diastolic blood pressure, mmHg Antihypertensive medication use, % Diabetes, % Current smoker, % Current drinker, % History of cardiovascular disease, % Serum HDL-cholesterol, mg/dL Serum triglycerides, mg/dL Serum aspartate aminotransferase (AST), IU/L Serum g-glutamyltranspeptidase (gGTP), IU/L Serum creatinine, mg/dL Glomerular filtration rate (GFR), mL/min/1.73 m2 Women Target persons, n Age Serum uric acid, mg/dL Carotid intima-media thickness (mean CIMT), mm Subclinical carotid atherosclerosis (mean CIMT 1.1 mm), % Carotid intima-media thickness (maximum CIMT), mm Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm), % Body mass index, kg/m2 Systolic blood pressure, mmHg Diastolic blood pressure, mmHg Antihypertensive medication use, % Diabetes, % Current smoker, % Current drinker, % History of cardiovascular disease, % Serum HDL-cholesterol, mg/dL Serum triglycerides, mg/dL Serum aspartate aminotransferase (AST), IU/L Serum g-glutamyltranspeptidase (gGTP), IU/L Serum creatinine, mg/dL Glomerular filtration rate (GFR), mL/min/1.73 m2
CKD
()
(þ)
1081 65.6 10.8 5.5 0.7 1.9 1.0 24.7 23.4 141 84 27.6 10.6 25.9 47.5 9.9 55 117 25 39 0.86 73.5
411 65.4 10.4 7.9 0.8 4.2 1.0 21.4 24.5 146 87 36.0 7.8 21.0 56.6 11.3 52 143 26 57 1.01 62.4
2324 63.4 11.4 4.7 0.7 1.4 0.9 15.6 22.9 141 82 28.8 5.8 3.4 10.0 6 62 115 22 24 0.68 70.1
317 68.1 10.2 7.7 0.7 5.0 0.9 15.3 24.4 144 84 44.0 8.0 6.3 17.1 7.5 58 138 24 32 0.82 59.1
p
()
(þ)
p
<0.001 0.031 0.016 0.177 0.198 <0.001 <0.001 <0.001 <0.001 0.105 0.047 0.002 0.410 <0.001 0.001 0.089 <0.001 <0.001 <0.001
1094 63.8 10.7 5.9 0.7 1.5 1.0 21.5 23.6 142 84 28.1 10.2 26.4 49.4 8.1 55 118 25 42 0.79 77.4
398 70.4 8.9 6.8 0.8 4.9 1.1 30.7 24.0 144 86 34.7 8.9 19.3 51.7 16.1 53 141 24 49 1.19 51.2
<0.001 <0.001 <0.001 <0.001 <0.001 0.012 0.262 0.005 0.013 0.494 0.006 0.435 <0.001 0.006 <0.001 0.024 0.049 <0.001 <0.001
<0.001 0.231 0.001 0.187 0.928 <0.001 <0.001 0.020 <0.001 0.122 0.013 <0.001 0.298 <0.001 <0.001 0.004 <0.001 <0.001 <0.001
1786 62.2 11.6 4.6 0.7 0.8 0.9 14.2 23.0 140 82 30.1 6.1 3.8 10.4 6.4 61 115 22 24 0.61 77.2
855 67.5 10.0 5.3 0.7 3.1 1.0 18.4 23.1 142 83 31.6 5.8 3.7 11.8 5.7 62 125 22 25 0.89 51.1
<0.001 <0.001 <0.001 <0.001 0.048 0.467 0.010 0.008 0.413 0.698 0.851 0.272 0.495 0.349 0.001 0.257 0.636 <0.001 <0.001
Age: mean standard deviation. Hyperuricemia: defined as serum uric acid > 7.0 mg/dL. CKD: defined as GFR < 60 mL/min/1.73 m2.
3.3. Association between serum uric acid concentration and GFR By using simple linear regression analysis, we found the serum concentration of uric acid correlated with GFR for both men and women: (r ¼ 0.34, p < 0.001) for men and (r ¼ 0.35, p < 0.001) for women. Similar associations were observed for participants both without CKD and with CKD: (r ¼ 0.25, p < 0.001) for men without CKD, and (r ¼ 0.26, p < 0.001) for men with CKD, while the corresponding values for women were (r ¼ 0.24, p < 0.001) and (r ¼ 0.28, p < 0.001). Since significant associations between serum uric acid concentration and GFR were observed even in the presence of CKD, we considered a CKD-stratified study not to be suitable for investigating the association between hyperuricemia and subclinical carotid atherosclerosis. 3.4. Association between subclinical carotid atherosclerosis and hyperuricemia Table 3 shows that hyperuricemia is a significant risk for subclinical carotid atherosclerosis with mean CIMT 1.1 mm for both
men and women, independent from classical risk factors except GFR. However, with further adjustment for GFR those significant associations became non-significant. For men, even classical risk factors except GFR do not show any significant associations with subclinical carotid atherosclerosis with maximum CIMT 1.1 mm, but after adjustment for GFR, the inverse association became significant. Essentially the same associations were observed for women. However, in the fully adjusted model (Model 3) this association did not reach significance. For a more detailed evaluation of the beneficial effects of subclinical carotid atherosclerosis, we performed further analyses of the participants without subclinical carotid atherosclerosis with mean CIMT 1.1 mm. For subclinical carotid atherosclerosis with mean CIMT <1.1 mm and maximum CIMT 1.1 mm, we found essentially the same associations as for subclinical carotid atherosclerosis with maximum CIMT 1.1 mm. The OR and 95%CI of subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) for men were 0.80(0.59e1.09) for Model 1, 0.75(0.55e1.03) for Model 2 and 0.62(0.44e0.86) for Model 3 and for women the corresponding values were 0.89(0.63e1.24), 0.82(0.57e1.16) and 0.74(0.51e1.06).
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Table 2 Odd ratios (OR) and 95% confidence intervals (CI) for risk of carotid atherosclerosis by chronic kidney disease (CKD). CKD ()
Table 3 Odds ratios (OR) and 95% confidence intervals (CI) for risk of carotid atherosclerosis by hyperuricemia.
p
Hyperuricemia
(þ)
Men Target persons (n) 1094 398 Subclinical carotid atherosclerosis (mean CIMT 1.1 mm) No. of cases (percentage) 15 (1.4) 21 (5.3) Model.1 1.00 3.09 (1.53e6.23) Model.2 1.00 2.71 (1.30e5.66) Model.3 1.00 1.00 (0.33e3.05) Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) No. of cases (percentage) 214 (19.6) 143 (35.9) Model.1 1.00 1.58 (1.20e2.06) Model.2 1.00 1.59 (1.20e2.11) Model.3 1.00 1.01 (0.67e1.51) Women Target persons (n) 1786 855 Subclinical carotid atherosclerosis (mean CIMT 1.1 mm) No. of cases (percentage) 12 (0.7) 29 (3.4) Model.1 1.00 3.80 (1.91e7.55) Model.2 1.00 3.51 (1.75e7.05) Model.3 1.00 1.58 (0.51e4.92) Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) No. of cases (percentage) 228 (12.8) 184 (21.5) Model.1 1.00 1.38 (1.10e1.73) Model.2 1.00 1.32 (1.05e1.66) Model.3 1.00 1.05 (0.73e1.51)
()
0.002 0.008 0.998
0.001 0.001 0.981
<0.001 <0.001 0.430
0.006 0.017 0.809
Model 1: Adjusted for age. Model 2: Model 1 þ further adjustment for systolic blood pressure, antihypertensive medication use, body mass index, smoking, alcohol intake, diabetes, history of cardiovascular disease, serum triglycerides, serum HDL cholesterol, serum aspartate aminotransferase (AST), and serum g-glutamyltranspeptidase (gGTP). Model 3: Model 2 þ further adjustment for GFR.
Men Target persons (n) Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3 Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3 Women Target persons (n) Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3 Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3
p (þ)
1081 411 (mean CIMT 1.1 mm) 19 (1.8) 17 (4.1) 1.00 2.50 (1.28e4.87) 1.00 2.20 (1.10e4.42) 1.00 1.54 (0.74e3.20) (maximum CIMT 1.1 mm) 265 (24.5) 92 (22.4) 1.00 0.91 (0.68e1.20) 1.00 0.84 (0.63e1.13) 1.00 0.67 (0.49e0.92) 2324 317 (mean CIMT 1.1 mm) 29 (1.2) 12 (3.8) 1.00 2.32 (1.16e4.64) 1.00 2.12 (1.02e4.38) 1.00 1.32 (0.61e2.88) (maximum CIMT 1.1 mm) 350 (15.1) 62 (19.6) 1.00 1.01 (0.74e1.38) 1.00 0.92 (0.66e1.27) 1.00 0.80 (0.57e1.12)
0.007 0.026 0.247
0.500 0.243 0.013
0.018 0.044 0.482
0.960 0.612 0.200
Hyperuricemia: Defined as serum uric acid>7.0 mg/dL. Model 1: Adjusted for age. Model 2 : Model 1 þ further adjustment for systolic blood pressure, antihypertensive medication use, body mass index, smoking, alcohol intake, diabetes, history of cardiovascular disease, serum triglycerides, serum HDL cholesterol, serum aspartate aminotransferase (AST), and serum g-glutamyltranspeptidase (gGTP). Model 3 : Model.2 þ further adjusted for GFR.
4. Discussion The major finding of the study presented here, which is based on findings for a rural community-dwelling Japanese population, is that, while hyperuricemia-related renal impairment is a significant marker for subclinical carotid atherosclerosis for both men and women, hyperiricemia per se may be inversely associated with subclinical carotid atherosclerosis for men. In terms of clinical application, this finding means that, to prevent the progression of atherosclerosis, the treatment target for hyperuricemia should be a disease underlying hyperuricemia, such as renal impairment, but not hyperuricemia itself. A strong association between renal impairment and hyperuricemia has been reported by previous studies [6,18]. Hyperuricemia might act as a marker of renal impairment since endothelial dysfunction has been recognized as one of the initial mechanisms which lead to glomerular injury [8] and atherosclerosis. Hyperuricemia, and especially renal impairment-related hyperuricemia, represents a significant risk of atherosclerosis. These findings are compatible with our results that showed for both men and women, that CKD and hyperuricemia constitute significant risks of subclinical carotid atherosclerosis with mean CIMT 1.1 mm, but after further adjustment for GFR those significant association became non-significant. However, the mechanisms that are responsible for the reduction by hyperuricemia in the risk of subclinical carotid atherosclerosis with maximum CIMT 1.1 mm, especially after adjustment of GFR, remain to be clarified. One consideration is that uric acid may protect against oxidative stress in atherosclerosis because it provides an antioxidant defense [3,4]. Nevertheless, hyperuricemia often occurs when renal function is reduced. The beneficial effect of hyperuricemia on carotid atherosclerosis thus seems to be masked by the effects of renal impairment. This would explain why the
beneficial effect of hyperuricemia was observed in our study only after adjustment for GFR. Furthermore, the severity of carotid atherosclerosis might be determined by the balance between the detriments resulting from atherosclerosis, which might be associated with hyperuricemia-related renal impairment and the possible beneficial effects on atherosclerosis by hyperuricemia per se. Moreover, subclinical carotid atherosclerosis (mean CIMT <1.1 mm and maximum CIMT 1.1 mm) may be much more sensitive for the beneficial effects of hyperuricemia than does subclinical carotid atherosclerosis with mean CIMT 1.1 mm because of the small lesions of atherosclerosis. Our further analysis of participants without subclinical carotid atherosclerosis with mean CIMT 1.1 mm, which clearly indicates the risk of subclinical carotid atherosclerosis (mean CIMT < 1.1 mm and maximum CIMT 1.1 mm), showed associations similar to those identified by the analysis of all subjects. Some potential limitations of this study warrant further consideration. Our fully-adjusted (including GFR) analysis showed significant inverse association of hyperuricemia per se on subclinical carotid atherosclerosis with maximum CIMT 1.1 mm for men but not for women. However, this analysis also showed essentially the same association for subclinical carotid atherosclerosis with maximum CIMT 1.1 mm for both men and women. Furthermore, data for menopausal status were not available. Since menopausal status has significant effects on CIMT [19] and serum uric acid [20], menopausal status might be an important determinant factor involving the association between subclinical carotid atherosclerosis and hyperuricemia. This indicates that further investigations with larger numbers of participants and including menopausal status data are needed. Moreover, because this is a cross-sectional study, causal relationships could not be established.
Y. Shimizu et al. / Atherosclerosis 233 (2014) 525e529
In conclusion, even though hyperuricemia-related renal impairment is a significant marker for subclinical carotid atherosclerosis for both men and women, our findings for a rural community-dwelling Japanese population indicate that hyperuricemia per se may be inversely associated with subclinical carotid atherosclerosis for men. Disclosure None. Acknowledgment This work was financially supported by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (No. 22370090). References [1] Gür M, Sahin DY, Elbasan Z, et al. Uric acid and high sensitive C-reactive protein are associated with subclinical thoracic aortic atherosclerosis. J Cardiol 2013;61:144e8. [2] Iribarren C, Folsom AR, Eckfeldt JH, et al. Correlates of uric acid and its association with asymptomatic carotid atherosclerosis: the ARIC study. Atherosclerosis Risk in Communities. Ann 1996;6:331e40. [3] Glantzounis GK, Tsimoyiannis EC, Kappas AM, et al. Uric acid and oxidative stress. Curr Pharm Des 2005;11:4145e51. [4] Stocker R, Keaney JE Jr. Role of oxidative modifications in atherosclerosis. Physiol Rev 2004;84:1381e478. [5] Miyaoka T, Mochizuki T, Takei T, et al. Serum uric acid levels and long-term outcomes in chronic kidney disease. Heart Vessels 2013 [E pub ahead of print]. [6] Ohno I. Relationship between hyperuricenmia and chronic kidney disease. Nucleosides Nucleotides Nucleic Acids 2011;30:1039e44.
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[7] Wang Y, Bao X. Effects of uric acid on endothelial dysfunction in early chronic kidney disease and its mechanisms. Eur J Med Res 2013;18:26. [8] Endemann DH, Schiffrin EL. Endothelial dysfunction. J Am Soc Nephrol 2004;15:1983e92. [9] Shimizu Y, Maeda K, Imanno H, et al. Chronic kidney disease and drinking status in relation to risks of stroke and its subtypes. The circulatory Risk in Communities Study (CIRCS). Stroke 2011;42:2531e7. [10] Imai E. Equation for estimating GFR from creatinine in Japan. Nihon Rinsho 2008;66:1725e9. [11] Imai E, Horio M, Watanabe T, et al. Prevalence of chronic kidney disease in the Japanese general population. Clin Exp Nephrol 2009;13:621e30. [12] American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2010;33:S62e9. [13] Yanase T, Nasu S, Mukuta Y, et al. Evaluation of a new carotid intima-media thickness measurement by B-mode ultrasonography using an innovative measurement software, intimasope. Am J Hypertens 2006;19:1206e12. [14] Hara T, Takamura N, Akashi S, et al. Evaluation of clinical markers of atherosclerosis in young and elderly Japanese adults. Clin Chem Lab Med 2006;44:824e9. [15] Kawamori R, Yamasaki Y, Matsushima H, et al. Prevalence of carotid atherosclerosis in diabetic patients. Ultrasound high-resolution B-mode imaging on carotid arteries. Diabetes Care 1992;15:1290e4. [16] Du HW, Li JY, He Y. Glycemic and blood pressure control in older patients with hypertension and diabetes: association with carotid atherosclerosis. J Geriatr Cardiol 2011;8:24e30. [17] Shimizu Y, Nakazato M, Sekita T, et al. Association of arterial stiffness and diabetes with triglycerides-to-HDL cholesterol ratio for Japanese men; the Nagasaki Islands Study. Atherosclerosis 2013;228:491e5. [18] Nashar K, Fried LF. Hyperuricemia and the progression of chronic kidney disease: is uric acid a marker or an independent risk factor? Adv Chronic Kidney Dis 2012;19:386e91. [19] Kablak-Ziembicka A, Przewlocki T, Tracz W, et al. Carotid intima-media thickness in pre- and postmenopausal women with suspected coronary artery disease. Heart Vessels 2008;23:295e300. [20] Shibata H, Matsuzaki T, Hatano S. Relationship of relevant factors of atherosclerosis to menopause in Japanese women. Am J Epidemiol 1979;109:420e4.
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Subclinical carotid atherosclerosis and hyperuricemia in relation to renal impairment in a rural Japanese population: The Nagasaki Islands study Yuji Shimizu a, *, Shimpei Sato a, Jun Koyamatsu b, Hirotomo Yamanashi b, Mami Tamai c, Koichiro Kadota a, Kazuhiko Arima d, Hironori Yamasaki e, Noboru Takamura f, Kiyoshi Aoyagi d, Takahiro Maeda a, b a
Department of Community Medicine, Nagasaki University Graduate School of Biomedical Science, Nagasaki, Japan Department of Island and Community Medicine, Nagasaki University Graduate School of Biomedical Science, Nagasaki, Japan c Unit of Translational Medicine, Department of Immunology and Rheumatology, Nagasaki University Graduate School of Biomedical Science, Nagasaki, Japan d Department of Public Health, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan e Center for Health and Community Medicine, Nagasaki University, Nagasaki, Japan f Department of Global Health, Medicine and Welfare, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 24 October 2013 Received in revised form 15 January 2014 Accepted 15 January 2014 Available online 27 January 2014
Objective: The influence of hyperuricemia on atherosclerosis is controversial. Subclinical carotid atherosclerosis can be defined in two ways in terms of mean and maximum carotid intima-media thickness (CIMT): one with mean CIMT 1.1 mm and the other with maximum CIMT 1.1 mm. However, no studies have been reported of the association between hyperuricemia and subclinical carotid atherosclerosis while taking the two different ways of classification into account. Methods: We conducted a cross-sectional study of 4133 subjects (1492 men and 2641 women) aged 30 e89 years undergoing general health check-ups. For analysis of various associations, we calculated the multivariable odds ratios (ORs) for the two ways classifications of subclinical carotid atherosclerosis in relation to hyperuricemia. Results: Hyperuricemia-related renal impairment constitutes a significant marker for subclinical carotid atherosclerosis with mean CIMT 1.1 mm for both men and women, while hyperuricemia per se was found to be beneficially associated with risk of subclinical carotid atherosclerosis with maximum CIMT 1.1 mm for men. The classical cardiovascular risk factors without adjustment for glomerular filtration rate (GFR) of ORs for subclinical carotid atherosclerosis (mean CIMT 1.1 mm) and subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) were 2.20(1.10e4.22) and 0.84(0.63e1.13) for men and 2.12(1.02e4.38) and 0.92(0.66e1.27) for women. After further adjustment for GFR, the corresponding values were 1.54(0.74e3.20) and 0.67(0.49e0.92) for men and 1.32(0.61e2.88) and 0.80(0.57 e1.12) for women. Conclusion: Hyperuricemia-related renal impairment is a significant marker for subclinical carotid atherosclerosis for both men and women, while hyperuricemia per se may be inversely associated with subclinical carotid atherosclerosis for men as seen in a rural community-dwelling Japanese population. Ó 2014 Elsevier Ireland Ltd. All rights reserved.
Keywords: CIMT Hyperuricemia Cross-sectional study
1. Introduction The influence of hyperuricemia on atherosclerosis remains a matter of debate. A previous sex-combined study with 181 participants who underwent transesophageal echocardiography reported that uric acid is independently and positively associated with subclinical thoracic atherosclerosis [1]. However, the * Corresponding author. E-mail address: [email protected] (Y. Shimizu). 0021-9150/$ e see front matter Ó 2014 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atherosclerosis.2014.01.033
Atherosclerosis Risk in Communities Study (ARIC Study) reported that uric acid per se may not be a risk factor for atherosclerosis [2]. In fact, another study hypothesized that uric acid generates an antioxidant defense in humans, so that it might offer protection against oxidative stress in atherosclerosis [3,4]. On the other hand, hyperuricemia is a well-known factor that is positively associated with various forms of renal impairment such as chronic kidney disease (CKD) [5,6] while renal impairment is also known to be associated with atherosclerosis [7,8] and stroke [9]. The beneficial effect on atherosclerosis might therefore be masked by a condition
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underlying hyperuricemia, which is associated with both hyperuricemia and atherosclerosis. This implies that a background of hyperuricemia, like renal impairment, may therefore often be associated with a systemically higher risk of atherosclerosis even though hyperuricemia per se has a protective effect on progression of minor atherosclerosis. While subclinical carotid atherosclerosis with mean CIMT 1.1 mm systemically indicates carotid atherosclerosis, subclinical carotid atherosclerosis with maximum CIMT 1.1 mm may have a strong effect on minor atherosclerosis. We hypothesized that hyperuricemia constitutes a marker of subclinical carotid atherosclerosis with mean CIMT 1.1 mm but has a beneficial effect on subclinical carotid atherosclerosis with maximum CIMT 1.1 mm and that these associations are strongly influenced by the renal condition. To investigate these associations, we performed a cross-sectional study of subjects undergoing general health check-ups. 2. Subjects and methods This study was approved by the Ethics Committee for Use of Humans of Nagasaki University (project registration number 0501120073). The survey population comprised 4269 participants (1538 men and 2731 women) aged 30e89 years, all residents of the western rural community of the Goto Islands, who participated in this study between 2005 and 2012. A total of 136 individuals (46 men and 90 women) with missing data were excluded, leaving 4133 participants (1492 men and 2641 women) for enrollment in this study. The mean age of the study population was 65.5 years (10.7 SD; range 30e89) for men and 63.9 years (11.4 SD; range 30e89) for women. Systolic and diastolic blood pressures at rest were recorded with a blood pressure measuring device (HEM-907; Omron, Kyoto, Japan). Body weight and height were measured with an automatic body composition analyzer (BF-220; Tanita, Tokyo, Japan) at the time of drawing blood. Fasting blood samples were obtained and the serum was separated and centrifuged after blood coagulation. Serum triglycerides, serum HDL-cholesterol, serum aspartate aminotransferase (AST), serum g-glutamyltranspeptidase (gGTP), serum creatinine, and HbA1c were measured with standard laboratory procedures. Trained interviewers obtained information on smoking status, drinking status, medical history, use of antihypertensive agents and of medication for diabetes mellitus. The glomerular filtration rate (GFR) was estimated with an established method with three variations recently proposed by a working group of the Japanese Chronic Kidney Disease Initiative [10]. According to this adaptation, GFR (mL/min/1.73 m2) ¼ 194 (serum creatinine (enzyme method))1.094 (age)0.287 (0.739 for women). CKD was defined as GFR <60 mL/min per 1.73 m2 in accordance with the National Kidney Disease Outcomes Quality Initiative guidelines [11]. HbA1c (as defined by NGSP, the National Glycohemoglobin Standardization Program) was calculated with the following equation, which was recently proposed by a working group of the Japanese Diabetes Society: (JDS): HbA1c(NGSP) ¼ HbA1c(JDS) þ 0.4%. Presence of diabetes was defined as HbA1c (NGSP) 6.5%, and/or initiation of glucose-lowering medication or insulin therapy [12]. Hyperuricemia was defined as a serum uric acid level >7 mg/dL. 2.1. Carotid B-mode ultrasound imaging Measurement of CIMT by ultrasonography of the left and right carotid arteries was performed by two medical doctors (N.T. and M.N.) using a LOGIQ Book XP with a 10-MHz transducer (GE Healthcare, Milwaukee, WI, USA) that was programmed with the IMT measurement software Intimascope (Cross Media Ltd., Tokyo,
Japan) [13]. The protocol used has been described in detail elsewhere [14]. Mean CIMT was calculated as the mean of right and left CIMT measurements with carotid plaques excluded, and maximum CIMT was defined as the highest CIMT measurement on either side. Since a previous study reported the normal CIMT value was <1.1 mm [15] and that of elevated CIMT value 1.1 mm [16], while a previous study of ours produced a definition of atherosclerosis as maximum CIMT 1.1 mm [17], we classified subclinical carotid atherosclerosis in two ways; subclinical carotid atherosclerosis with mean CIMT 1.1 mm and subclinical carotid atherosclerosis with maximum CIMT 1.1 mm. Intra-observer variation agreement for CIMT (N.T., n ¼ 32) was 0.91 (p < 0.01), and interobserver variation agreement (N.T. vs. M.N., n ¼ 41) was 0.78 (p < 0.01). 2.2. Statistical analysis Differences in age-adjusted mean values or prevalence of potential confounding factors according to CKD category and hyperuricemia category were analyzed by using covariance or general linear models, and logistic regression models were used for calculating odds ratios (ORs) and 95% confidence intervals (CIs) for associations with subclinical carotid atherosclerosis. Three different approaches were used for making adjustments for confounding factors. First, the data were adjusted only for age (Model 1). Second, we included other possible confounding factors, namely smoking status (never smoker, former smoker, current smoker), alcohol intake [non-drinker, current light to moderate drinker (1e6 times/week), current heavy drinker (every day)], systolic blood pressure (mmHg), antihypertensive medication use (no, yes), history of cardiovascular disease (no, yes), diabetes (no, yes), body mass index (kg/m2), serum triglyceride (mg/dL), serum HDL-cholesterol (mg/dL), AST (IU/L), and g-GTP (IU/L) (Model 2). Third, we made further adjustments for GFR (Model 3). All statistical analyses were performed with the SAS system for Windows (version 9.3; SAS Inc., Cary, NC). All p-values for statistical tests were two-tailed, and values of <0.05 were regarded as statistically significant. 3. Results 3.1. Characteristics of the study population Table 1 shows sex-specific characteristics of the study population by CKD and hyperuricemia status. Of the 1492 men and 2641 women, 398 and 855, respectively, were diagnosed with CKD, and the corresponding number for diagnosis of hyperuricemia were 411 and 317. Overall, both male and female participants with CKD or hyperuricemia proved to have higher cardiovascular risk factors than those without either of these abnormalities. 3.2. Association between subclinical carotid atherosclerosis and CKD Table 2 shows the association between subclinical carotid atherosclerosis and CKD. Regardless of classical cardiovascular risk factors, CKD constitutes a significant risk for subclinical carotid atherosclerosis with mean CIMT 1.1 mm for both men and women, but after further adjustment for GFR, this association no longer held. Essentially the same association was observed for subclinical carotid atherosclerosis with maximum CIMT 1.1 mm.
Y. Shimizu et al. / Atherosclerosis 233 (2014) 525e529
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Table 1 Sex-specific clinical characteristics of the study population with chronic kidney disease (CKD) and hyperuricemia. Hyperuricemia
Men Target persons, n Age Serum uric acid, mg/dL Carotid intima-media thickness (mean CIMT), mm Subclinical carotid atherosclerosis (mean CIMT 1.1 mm), % Carotid intima-media thickness (maximum CIMT), mm Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm), % Body mass index, kg/m2 Systolic blood pressure, mmHg Diastolic blood pressure, mmHg Antihypertensive medication use, % Diabetes, % Current smoker, % Current drinker, % History of cardiovascular disease, % Serum HDL-cholesterol, mg/dL Serum triglycerides, mg/dL Serum aspartate aminotransferase (AST), IU/L Serum g-glutamyltranspeptidase (gGTP), IU/L Serum creatinine, mg/dL Glomerular filtration rate (GFR), mL/min/1.73 m2 Women Target persons, n Age Serum uric acid, mg/dL Carotid intima-media thickness (mean CIMT), mm Subclinical carotid atherosclerosis (mean CIMT 1.1 mm), % Carotid intima-media thickness (maximum CIMT), mm Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm), % Body mass index, kg/m2 Systolic blood pressure, mmHg Diastolic blood pressure, mmHg Antihypertensive medication use, % Diabetes, % Current smoker, % Current drinker, % History of cardiovascular disease, % Serum HDL-cholesterol, mg/dL Serum triglycerides, mg/dL Serum aspartate aminotransferase (AST), IU/L Serum g-glutamyltranspeptidase (gGTP), IU/L Serum creatinine, mg/dL Glomerular filtration rate (GFR), mL/min/1.73 m2
CKD
()
(þ)
1081 65.6 10.8 5.5 0.7 1.9 1.0 24.7 23.4 141 84 27.6 10.6 25.9 47.5 9.9 55 117 25 39 0.86 73.5
411 65.4 10.4 7.9 0.8 4.2 1.0 21.4 24.5 146 87 36.0 7.8 21.0 56.6 11.3 52 143 26 57 1.01 62.4
2324 63.4 11.4 4.7 0.7 1.4 0.9 15.6 22.9 141 82 28.8 5.8 3.4 10.0 6 62 115 22 24 0.68 70.1
317 68.1 10.2 7.7 0.7 5.0 0.9 15.3 24.4 144 84 44.0 8.0 6.3 17.1 7.5 58 138 24 32 0.82 59.1
p
()
(þ)
p
<0.001 0.031 0.016 0.177 0.198 <0.001 <0.001 <0.001 <0.001 0.105 0.047 0.002 0.410 <0.001 0.001 0.089 <0.001 <0.001 <0.001
1094 63.8 10.7 5.9 0.7 1.5 1.0 21.5 23.6 142 84 28.1 10.2 26.4 49.4 8.1 55 118 25 42 0.79 77.4
398 70.4 8.9 6.8 0.8 4.9 1.1 30.7 24.0 144 86 34.7 8.9 19.3 51.7 16.1 53 141 24 49 1.19 51.2
<0.001 <0.001 <0.001 <0.001 <0.001 0.012 0.262 0.005 0.013 0.494 0.006 0.435 <0.001 0.006 <0.001 0.024 0.049 <0.001 <0.001
<0.001 0.231 0.001 0.187 0.928 <0.001 <0.001 0.020 <0.001 0.122 0.013 <0.001 0.298 <0.001 <0.001 0.004 <0.001 <0.001 <0.001
1786 62.2 11.6 4.6 0.7 0.8 0.9 14.2 23.0 140 82 30.1 6.1 3.8 10.4 6.4 61 115 22 24 0.61 77.2
855 67.5 10.0 5.3 0.7 3.1 1.0 18.4 23.1 142 83 31.6 5.8 3.7 11.8 5.7 62 125 22 25 0.89 51.1
<0.001 <0.001 <0.001 <0.001 0.048 0.467 0.010 0.008 0.413 0.698 0.851 0.272 0.495 0.349 0.001 0.257 0.636 <0.001 <0.001
Age: mean standard deviation. Hyperuricemia: defined as serum uric acid > 7.0 mg/dL. CKD: defined as GFR < 60 mL/min/1.73 m2.
3.3. Association between serum uric acid concentration and GFR By using simple linear regression analysis, we found the serum concentration of uric acid correlated with GFR for both men and women: (r ¼ 0.34, p < 0.001) for men and (r ¼ 0.35, p < 0.001) for women. Similar associations were observed for participants both without CKD and with CKD: (r ¼ 0.25, p < 0.001) for men without CKD, and (r ¼ 0.26, p < 0.001) for men with CKD, while the corresponding values for women were (r ¼ 0.24, p < 0.001) and (r ¼ 0.28, p < 0.001). Since significant associations between serum uric acid concentration and GFR were observed even in the presence of CKD, we considered a CKD-stratified study not to be suitable for investigating the association between hyperuricemia and subclinical carotid atherosclerosis. 3.4. Association between subclinical carotid atherosclerosis and hyperuricemia Table 3 shows that hyperuricemia is a significant risk for subclinical carotid atherosclerosis with mean CIMT 1.1 mm for both
men and women, independent from classical risk factors except GFR. However, with further adjustment for GFR those significant associations became non-significant. For men, even classical risk factors except GFR do not show any significant associations with subclinical carotid atherosclerosis with maximum CIMT 1.1 mm, but after adjustment for GFR, the inverse association became significant. Essentially the same associations were observed for women. However, in the fully adjusted model (Model 3) this association did not reach significance. For a more detailed evaluation of the beneficial effects of subclinical carotid atherosclerosis, we performed further analyses of the participants without subclinical carotid atherosclerosis with mean CIMT 1.1 mm. For subclinical carotid atherosclerosis with mean CIMT <1.1 mm and maximum CIMT 1.1 mm, we found essentially the same associations as for subclinical carotid atherosclerosis with maximum CIMT 1.1 mm. The OR and 95%CI of subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) for men were 0.80(0.59e1.09) for Model 1, 0.75(0.55e1.03) for Model 2 and 0.62(0.44e0.86) for Model 3 and for women the corresponding values were 0.89(0.63e1.24), 0.82(0.57e1.16) and 0.74(0.51e1.06).
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Table 2 Odd ratios (OR) and 95% confidence intervals (CI) for risk of carotid atherosclerosis by chronic kidney disease (CKD). CKD ()
Table 3 Odds ratios (OR) and 95% confidence intervals (CI) for risk of carotid atherosclerosis by hyperuricemia.
p
Hyperuricemia
(þ)
Men Target persons (n) 1094 398 Subclinical carotid atherosclerosis (mean CIMT 1.1 mm) No. of cases (percentage) 15 (1.4) 21 (5.3) Model.1 1.00 3.09 (1.53e6.23) Model.2 1.00 2.71 (1.30e5.66) Model.3 1.00 1.00 (0.33e3.05) Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) No. of cases (percentage) 214 (19.6) 143 (35.9) Model.1 1.00 1.58 (1.20e2.06) Model.2 1.00 1.59 (1.20e2.11) Model.3 1.00 1.01 (0.67e1.51) Women Target persons (n) 1786 855 Subclinical carotid atherosclerosis (mean CIMT 1.1 mm) No. of cases (percentage) 12 (0.7) 29 (3.4) Model.1 1.00 3.80 (1.91e7.55) Model.2 1.00 3.51 (1.75e7.05) Model.3 1.00 1.58 (0.51e4.92) Subclinical carotid atherosclerosis (maximum CIMT 1.1 mm) No. of cases (percentage) 228 (12.8) 184 (21.5) Model.1 1.00 1.38 (1.10e1.73) Model.2 1.00 1.32 (1.05e1.66) Model.3 1.00 1.05 (0.73e1.51)
()
0.002 0.008 0.998
0.001 0.001 0.981
<0.001 <0.001 0.430
0.006 0.017 0.809
Model 1: Adjusted for age. Model 2: Model 1 þ further adjustment for systolic blood pressure, antihypertensive medication use, body mass index, smoking, alcohol intake, diabetes, history of cardiovascular disease, serum triglycerides, serum HDL cholesterol, serum aspartate aminotransferase (AST), and serum g-glutamyltranspeptidase (gGTP). Model 3: Model 2 þ further adjustment for GFR.
Men Target persons (n) Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3 Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3 Women Target persons (n) Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3 Subclinical carotid atherosclerosis No. of cases (percentage) Model.1 Model.2 Model.3
p (þ)
1081 411 (mean CIMT 1.1 mm) 19 (1.8) 17 (4.1) 1.00 2.50 (1.28e4.87) 1.00 2.20 (1.10e4.42) 1.00 1.54 (0.74e3.20) (maximum CIMT 1.1 mm) 265 (24.5) 92 (22.4) 1.00 0.91 (0.68e1.20) 1.00 0.84 (0.63e1.13) 1.00 0.67 (0.49e0.92) 2324 317 (mean CIMT 1.1 mm) 29 (1.2) 12 (3.8) 1.00 2.32 (1.16e4.64) 1.00 2.12 (1.02e4.38) 1.00 1.32 (0.61e2.88) (maximum CIMT 1.1 mm) 350 (15.1) 62 (19.6) 1.00 1.01 (0.74e1.38) 1.00 0.92 (0.66e1.27) 1.00 0.80 (0.57e1.12)
0.007 0.026 0.247
0.500 0.243 0.013
0.018 0.044 0.482
0.960 0.612 0.200
Hyperuricemia: Defined as serum uric acid>7.0 mg/dL. Model 1: Adjusted for age. Model 2 : Model 1 þ further adjustment for systolic blood pressure, antihypertensive medication use, body mass index, smoking, alcohol intake, diabetes, history of cardiovascular disease, serum triglycerides, serum HDL cholesterol, serum aspartate aminotransferase (AST), and serum g-glutamyltranspeptidase (gGTP). Model 3 : Model.2 þ further adjusted for GFR.
4. Discussion The major finding of the study presented here, which is based on findings for a rural community-dwelling Japanese population, is that, while hyperuricemia-related renal impairment is a significant marker for subclinical carotid atherosclerosis for both men and women, hyperiricemia per se may be inversely associated with subclinical carotid atherosclerosis for men. In terms of clinical application, this finding means that, to prevent the progression of atherosclerosis, the treatment target for hyperuricemia should be a disease underlying hyperuricemia, such as renal impairment, but not hyperuricemia itself. A strong association between renal impairment and hyperuricemia has been reported by previous studies [6,18]. Hyperuricemia might act as a marker of renal impairment since endothelial dysfunction has been recognized as one of the initial mechanisms which lead to glomerular injury [8] and atherosclerosis. Hyperuricemia, and especially renal impairment-related hyperuricemia, represents a significant risk of atherosclerosis. These findings are compatible with our results that showed for both men and women, that CKD and hyperuricemia constitute significant risks of subclinical carotid atherosclerosis with mean CIMT 1.1 mm, but after further adjustment for GFR those significant association became non-significant. However, the mechanisms that are responsible for the reduction by hyperuricemia in the risk of subclinical carotid atherosclerosis with maximum CIMT 1.1 mm, especially after adjustment of GFR, remain to be clarified. One consideration is that uric acid may protect against oxidative stress in atherosclerosis because it provides an antioxidant defense [3,4]. Nevertheless, hyperuricemia often occurs when renal function is reduced. The beneficial effect of hyperuricemia on carotid atherosclerosis thus seems to be masked by the effects of renal impairment. This would explain why the
beneficial effect of hyperuricemia was observed in our study only after adjustment for GFR. Furthermore, the severity of carotid atherosclerosis might be determined by the balance between the detriments resulting from atherosclerosis, which might be associated with hyperuricemia-related renal impairment and the possible beneficial effects on atherosclerosis by hyperuricemia per se. Moreover, subclinical carotid atherosclerosis (mean CIMT <1.1 mm and maximum CIMT 1.1 mm) may be much more sensitive for the beneficial effects of hyperuricemia than does subclinical carotid atherosclerosis with mean CIMT 1.1 mm because of the small lesions of atherosclerosis. Our further analysis of participants without subclinical carotid atherosclerosis with mean CIMT 1.1 mm, which clearly indicates the risk of subclinical carotid atherosclerosis (mean CIMT < 1.1 mm and maximum CIMT 1.1 mm), showed associations similar to those identified by the analysis of all subjects. Some potential limitations of this study warrant further consideration. Our fully-adjusted (including GFR) analysis showed significant inverse association of hyperuricemia per se on subclinical carotid atherosclerosis with maximum CIMT 1.1 mm for men but not for women. However, this analysis also showed essentially the same association for subclinical carotid atherosclerosis with maximum CIMT 1.1 mm for both men and women. Furthermore, data for menopausal status were not available. Since menopausal status has significant effects on CIMT [19] and serum uric acid [20], menopausal status might be an important determinant factor involving the association between subclinical carotid atherosclerosis and hyperuricemia. This indicates that further investigations with larger numbers of participants and including menopausal status data are needed. Moreover, because this is a cross-sectional study, causal relationships could not be established.
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In conclusion, even though hyperuricemia-related renal impairment is a significant marker for subclinical carotid atherosclerosis for both men and women, our findings for a rural community-dwelling Japanese population indicate that hyperuricemia per se may be inversely associated with subclinical carotid atherosclerosis for men. Disclosure None. Acknowledgment This work was financially supported by a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (No. 22370090). References [1] Gür M, Sahin DY, Elbasan Z, et al. Uric acid and high sensitive C-reactive protein are associated with subclinical thoracic aortic atherosclerosis. J Cardiol 2013;61:144e8. [2] Iribarren C, Folsom AR, Eckfeldt JH, et al. Correlates of uric acid and its association with asymptomatic carotid atherosclerosis: the ARIC study. Atherosclerosis Risk in Communities. Ann 1996;6:331e40. [3] Glantzounis GK, Tsimoyiannis EC, Kappas AM, et al. Uric acid and oxidative stress. Curr Pharm Des 2005;11:4145e51. [4] Stocker R, Keaney JE Jr. Role of oxidative modifications in atherosclerosis. Physiol Rev 2004;84:1381e478. [5] Miyaoka T, Mochizuki T, Takei T, et al. Serum uric acid levels and long-term outcomes in chronic kidney disease. Heart Vessels 2013 [E pub ahead of print]. [6] Ohno I. Relationship between hyperuricenmia and chronic kidney disease. Nucleosides Nucleotides Nucleic Acids 2011;30:1039e44.
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