Hemodialysis patients are at an increased risk for

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1 Regional Arterial Stiffness in Patients with Type 2 Diabetes and Chronic Kidney Disease Eiji Kimoto, Tetsuo Shoji, Kayo Shinohara, Sawako Hatsuda, Katsuhito Mori, Shinya Fukumoto, Hidenori Koyama, Masanori Emoto, Yasuhisa Okuno, and Yoshiki Nishizawa Department of Metabolism, Endocrinology and Molecular Medicine, Osaka City University Graduate School of Medicine, Osaka, Japan Increased arterial stiffness is an independent predictor of death from cardiovascular disease, and aortic stiffness is more predictive than stiffness of other arterial regions. Because little is known about the effect of chronic kidney disease (CKD) on regional arterial stiffness, pulse wave velocity (PWV) of four different arterial segments was measured in patients who had type 2 diabetes with and without various stages of CKD. A total of 434 patients had type 2 diabetes, and there were 192 healthy control subjects who were comparable in age and gender. GFR was estimated by the abbreviated Modification of Diet in Renal Disease equation. The patients with diabetes were classified into CKD stages by the definition of the Kidney Disease Outcomes Quality Initiative guidelines. PWV was measured in the heart-femoral, heart-carotid, heart-brachial, and femoralankle segments simultaneously using an automatic pulse wave analyzer. PWV of each arterial region was increased in patients who had diabetes without kidney damage and was increased further in a stepwise manner with the advanced stages of CKD. The increase in PWV was greater in the heart-femoral and heart-carotid regions than in the heart-brachial and femoral-ankle segments. However, after adjustment for age, BP, and other confounding factors using a multiple regression model, decreased GFR was independently associated with increased PWV of the heart-femoral region but not with PWV of other arterial segments. In type 2 diabetes, CKD was associated with increased stiffness of arteries, particularly of the aorta. The cross-sectional result may explain the increased risk for cardiovascular disease in CKD, although longitudinal studies are needed to confirm it. J Am Soc Nephrol 17: , doi: /ASN Hemodialysis patients are at an increased risk for death from cardiovascular disease (CVD) (1 3), and those with diabetes have a further elevated risk for CVD (4). The poorer prognosis in hemodialysis patients with diabetes are explained, at least partly, by the more advanced thickening (5) and stiffening (6) of large arteries. In fact, these vascular changes are significant and independent predictors for CVD mortality in hemodialysis populations (6,7). A recent study (8) showed that the CVD risk increases in a stepwise manner as GFR declines. We showed that predialysis patients with advanced stages of chronic kidney disease (CKD) have increased arterial thickness (9,10) and stiffness (11). Recent studies (12 14) revealed a stepwise increase in arterial stiffness as a function of decreased GFR or the stages of CKD. CKD itself, rather than hemodialysis, is a strong risk factor for atherosclerotic vascular changes and CVD. The function and the structure of the vascular system is heterogeneous, and there is a marked difference between large central Received October 7, Accepted May 29, Published online ahead of print. Publication date available at Address correspondence to: Dr. Tetsuo Shoji, Department of Metabolism, Endocrinology and Molecular Medicine, Osaka City University Graduate School of Medicine, 1-4-3, Asahi-machi, Abeno-ku, Osaka , Japan. Phone: ; Fax: ; t-shoji@med.osaka-cu.ac.jp (elastic) arteries and smaller peripheral (muscular) arteries. The former represents the principal capacitive system, whereas the latter plays a major role in conduit function (15). London et al. (16) reported that the increase in arterial stiffness among hemodialysis patients was more significant for the central than the peripheral arteries. We recently showed that patients who have type 2 diabetes but without renal complications have preferential stiffening in central over peripheral arteries by measuring pulse wave velocity (PWV) in different regions of the arterial tree (17). In the same study, aging was associated with increased stiffness of central arteries more strongly than that of peripheral arteries. In contrast, gender affected PWV of the leg arteries. Therefore, different factors are involved in regional arterial stiffness. Also, stiffness of different arterial regions has different power in predicting CVD death, as recently shown in hemodialysis patients (18). So far, however, no study has examined the effect of decreased GFR or stages of CKD on regional arterial stiffness. In this study, we evaluated the effects of CKD on regional arterial stiffness by measuring PWV of four different arterial segments in patients with type 2 diabetes and various stages of CKD. Materials and Methods Patients A total of 434 patients had type 2 diabetes, and there were 192 healthy control subjects. They gave informed consent to participate in the study. Copyright 2006 by the American Society of Nephrology ISSN: /

2 2246 Journal of the American Society of Nephrology J Am Soc Nephrol 17: , 2006 CKD was defined as either kidney damage or GFR 60 ml/min per 1.73 m 2 according to the Kidney Disease Outcomes Quality Initiative Clinical Practice Guidelines (19). Increased urinary albumin/creatinine ratio 30 mg/g was used as evidence of kidney damage (20). The GFR was calculated by the abbreviated version of the Modification of Diet in Renal Disease (MDRD) study equation (19) GFR (ml/min per 1.73 m 2 ) 186 SCr age (if female), where SCr is serum creatinine concentration in mg/dl. Diagnosis of diabetes was made according to the American Diabetes Association criteria (21). We excluded those who had type 1 diabetes and were positive for GAD antibody, had a history of ketoacidosis, or were dependent on insulin therapy for survival. Gestational diabetes and diabetes associated with specific syndrome were carefully ruled out by their history. The healthy control subjects were screened from participants of a local health check program in Osaka City. Exclusion criteria were fasting plasma glucose level 7.0 mmol/l (126 mg/dl); kidney damage defined as urinary albumin/creatinine ratio 30 mg/g and/or decreased estimated GFR 60 ml/min per 1.73 m 2 ; liver dysfunction defined as AST 50 IU/L; current medication for diabetes, hypertension, and/or dyslipidemia; and history of myocardial infarction and/or cerebral infarction. Because hemodynamically significant stenosis of leg arteries affects PWV of the lower extremities (22), we excluded those who had reduced ankle-brachial pressure index (ABI) 0.9 from the total participants. PWV and BP Measurement PWV and BP were measured in the supine position after 5 min of bed rest using an automatic waveform analyzer (model BP-203RPE; Colin, Komaki, Japan) as described previously (17). Pressure waveforms of the brachial and tibial arteries were recorded by an oscillometric method using the occlusion/sensing cuffs adapted to both arms and both ankles. Pressure waveforms of the carotid and femoral arteries were recorded using multielement tonometry sensors placed at the left carotid and the left femoral arteries. Electrocardiogram was monitored with electrodes placed on both wrists. Heart sounds S1 and S2 were detected by a microphone set on the left edge of the sternum at the third intercostal space. The waveform analyzer measures time intervals between S2 and the notch of carotid pulse wave (Thc), between S2 and the notch of brachial pulse wave (Thb), between pulse waves of the carotid and femoral arteries (Tcf), and between pulse waves of the femoral and tibial (ankle) arteries (Tfa). The sum of Thc and Tcf gives the time for pulse waves to travel form the heart (aortic orifice) to the femoral artery (Thf). Also, the waveform analyzer estimates the path lengths of the heart-carotid (Dhc), the heart-brachial (Dhb), the heart-femoral (Dhf), and the femoral-ankle (Dfa) segments on the basis of height (HT, in cm) using the following formulas: Dhc HT ; Dhb HT ; Dhf HT ; and Dfa HT PWV was calculated for each arterial segment as the path length divided by the corresponding time interval. This method allowed us to perform simultaneous and automated measurements of PWV for the four arterial segments. This is a great advantage over other methods that require manual and consecutive measurements of pulse wave transit times from one site to another. Reproducibility of the automated PWV measurement was excellent as shown by the coefficients of variation (CV) of 6.0, 3.3, 4.9, and 3.3% for hc PWV, hb PWV, hf PWV, and fa PWV, respectively, when evaluated by repeating measurements in 17 healthy subjects on two different occasions. Blood Sampling and Measurements Blood was drawn in the morning after an overnight fast for at least 12 h. Serum creatinine was measured by an enzymatic method. Hemoglobin A1c was measured by HPLC, and plasma glucose was measured by a glucose oxidase method. Other measurements were done by routine laboratory methods. Statistical Analyses Results were summarized as mean SE. One-way ANOVA was used to assess the difference in mean values between groups, and then a post hoc test was performed by Scheffe-type multiple comparison test. Two-way ANOVA was used to evaluate effects of two categorical variables on one continuous variable. The difference in prevalence was assessed by 2 test. The correlation between two variables was examined by linear regression analysis. Independent association between the variables was assessed by multiple regression analysis. P 0.05 was taken as statistically significant. All calculations were performed by a personal computer using statistics software (Statview5 for Windows; SAS Institute Inc., Cary, NC). Results Characteristics of Participants Table 1 summarizes the characteristics of the six groups of participants. These groups were comparable in age and gender. Parameters of glycemia and renal function were significantly different by definition. Also, there was significant difference in BP; plasma lipids; smoking habit; and the use of medications for hypertension, dyslipidemia, and diabetes. Effects of CKD on PWV of the Four Arterial Segments PWV was compared among the six groups for each arterial region (Table 2). As compared with the healthy control group, the patients who had diabetes without CKD had significantly increased hf PWV (Figure 1, top), and it was increased further as the CKD stages were advanced. The same was true for hc PWV, hb PWV and fa PWV. When the healthy subjects were excluded, the effect of CKD stages on PWV within the patients with diabetes again was significant for hf PWV, hc PWV and hb PWV but not for fa PWV (data not shown). Different Influence of CKD on Regional PWV Because absolute values of PWV were different among the four segments of artery, it was difficult to compare directly the effect of CKD on PWV in different arterial regions. Blacher et al. (23) calculated a PWV index (difference between actual PWV from the theoretical PWV predicted by age, gender, BP, and pulse rate) for carotid-femoral PWV. However, it still was inappropriate for comparison of PWV among different arterial segments. Then, we expressed regional PWV values of each patient with diabetes as percentages relative to the corresponding mean PWV value of the healthy subjects, and the standardized PWV values were compared among the patients with diabetes in different stages of CKD (Figure 2). The effect of CKD stages and the effect of arterial regions on the standardized PWV both were significant by two-way ANOVA, but the effect of CKD stages was significantly different among the four regions as indicated by the presence of significant interaction between the effects of CKD stages and arterial regions. Thus,

3 J Am Soc Nephrol 17: , 2006 Regional PWV in Patients with Diabetes and CKD 2247 Table 1. Participants a Healthy DMnonCKD DMCKD1 DMCKD2 DMCKD3 DMCKD4 5 P n Gender (male/female) 97/95 136/104 65/36 27/16 10/12 15/ Age (yr) b SBP (mmhg) b b b,e b,c,d b,c,d DBP (mmhg) PP (mmhg) b 53 1 b 55 2 b 68 2 b,c,d,e 72 3 b,c,d,e BMI (kg/m 2 ) SCr (mg/dl) b b c,d b,c,d,e b,c,d,e,f GFR (ml/min per 1.73 m 2 ) b b b,c,d b,c,d,e b,c,d,e,f Hemoglobin (g/dl) FPG (mg/dl) b b b b d HbA 1 c (%) b b b b b,c,d TC (mg/dl) c TG (mg/dl) HDL cholesterol (mg/dl) b b b b Non-HDL cholesterol (mg/dl) Smoker (%) Medications (%) CCB ACEI ARB , -, or blockers diuretics statins glitazones a Data are mean SEM. ARB, angiotensin II receptor blocker; ACEI, angiotensin II converting enzyme inhibitors; BMI, body mass index; CCB, calcium channel blockers; DBP, diastolic BP; DMCKD1 5, patients who had diabetes and stages 1 through 5 CKD, respectively; DMnonCKD, patients who had diabetes without chronic kidney disease (CKD); FPG, fasting plasma glucose; HbA 1 c, hemoglobin A1c; SBP, systolic BP; SCr, serum creatinine; TC, total cholesterol; TG, triglycerides. b P 0.05 versus healthy control subjects. c P 0.05 versus DMnonCKD. d P 0.05 versus DMCKD1. e P 0.05 versus DMCKD2. f P 0.05 versus DMCKD3. Table 2. Regional PWV values in each stage of CKD a Healthy DMnonCKD DMCKD1 DMCKD2 DMCKD3 DMCKD4 5 P hf PWV b b,c b,c b,c,d b,c,d hc PWV b b b b hb PWV b b b,c b,c b,c fa PWV b b b a Data are mean SEM of regional PWV in the six groups, and the effect of CKD stages on regional PWV was evaluated by ANOVA. fa, femoral-ankle segment; hb, heart-brachial segment; hc, heart-carotid segment; hf, heart-femoral segment; PWV, pulse wave velocity. b P 0.05 versus healthy control subjects. c P 0.05 versus DMnonCKD. d P 0.05 versus DMCKD1 by Scheffe-type multiple comparison. the magnitude of the influence of CKD on PWV was not the same among the four arterial regions, and it was the largest in hf PWV and the smallest in fa PWV. Simple Regression Analysis of Factors Affecting Regional PWV Factors that correlated with PWV in the four arterial segments in all participants were examined by simple regression analysis (Table 3). A reduced GFR correlated significantly with increased PWV in the heart-femoral (Figure 1, bottom), heart-carotid, and heart-brachial segments but not in the femoral-ankle region. The r value was the largest for the hf PWV. Presence of diabetes, age, and systolic BP were significant factors that were associated with increased PWV of the four arterial regions. Multiple Regression Analysis of Factors Affecting Regional PWV Multiple regression analysis was performed to examine whether reduced GFR was an independent factor that affected

4 2248 Journal of the American Society of Nephrology J Am Soc Nephrol 17: , 2006 Figure 2. Different magnitude of influence of CKD on regional arterial stiffness. For comparing the magnitude of influence of CKD on stiffness of the four different arterial segments in patients with diabetes, regional PWV values were expressed as percentages relative to the corresponding healthy control mean level and plotted against CKD stages. The effects of CKD stages and arterial regions were evaluated by two-way ANOVA. Note that there was significant interaction between the effects of CKD stages and the arterial regions, indicating that the effect of CKD stages on PWV was different among the arterial regions. Mean SE. hc, heart-carotid; hb, heart-brachial; fa, femoralankle. Figure 1. Heart-femoral pulse wave velocity (hf PWV) as a function of chronic kidney disease (CKD) stages and GFR. (Top) Effect of CKD stages on regional PWV was evaluated by ANOVA. a P 0.05 versus the healthy controls; b P 0.05 versus DMnonCKD; c P 0.05 versus DMCKD1 by Scheffe-type multiple comparison. Mean SE. (Bottom) Correlation between GFR and hf PWV. E, healthy subjects; F, patients with diabetes; DMnonCKD, patients who have diabetes without CKD; DM- CKD1 5, patients who have diabetes and CKD stages 1 through 5, respectively. regional PWV in all participants (Table 4). After adjustment for age, gender, smoking, BP, lipids, and the presence of diabetes, reduced GFR was significantly associated with increased PWV of the heart-femoral segment but not with PWV of other arterial regions. Age and systolic BP were significant factors associated with increased PWV in the four arterial segments. The effect of the presence of diabetes on PWV was significant in the four arterial segments studied. Non HDL cholesterol was the significant factor associated with hf PWV. These models explained 24.3 to 54.7% of variance in regional PWV of the four arterial segments (Table 4). To examine possible influences of medications and anemia on the inverse association between GFR and hf PWV, we performed further analyses using multiple regression models in the patients with diabetes (Table 5). The first model showed that the association between GFR and hf PWV was significant when the effects of medications were not considered. Then, the use of statins (model 2), pioglitazone (model 3), or antihypertensives (model 4) was added as another covariate, but none of these covariates or the combination of them (model 5) had significant association with hf PWV. When calcium channel blockers, angiotensin-converting enzyme inhibitors, and angiotensin II receptor blockers were analyzed separately, no significant association was found independent of BP and other factors (data not shown). Even after these adjustments, the inverse association between GFR and hf PWV remained significant. In the final model (model 6) to which the level of hemoglobin was added further as the 12th covariate, hemoglobin was not a significant factor in the model. Also, the association of GFR with hf PWV was no longer significant. Correlation of Pulse Pressure with Regional PWV Because pulse pressure is a crude index of arterial stiffness, we calculated correlation coefficients between pulse pressure and each regional PWV in all participants. It was 0.545, 0.273, 0.481, and (P for all) for hf PWV, hc PWV, hb PWV, and fa PWV, respectively. Discussion Patients who are on hemodialysis are at a very high risk for death from CVD. A recent study (8) revealed that predialysis patients with CKD show a stepwise increase in the risk for CVD. Our study showed in patients with type 2 diabetes that arterial stiffness as measured by PWV was higher in those with more advanced stages of CKD. More important, we showed for the first time that there was a significant regional difference in the degree of arterial stiffening associated with CKD and that a reduced GFR had the strongest impact on PWV of the aorta among the four arterial regions studied. There are only a few studies on arterial stiffness in patients with diabetes and CKD. We (24) previously found in patients who had type 2 diabetes with and without microalbuminuria that the stiffness of the carotid artery was associated with GFR but not with albuminuria, independent of other clinical factors.

5 J Am Soc Nephrol 17: , 2006 Regional PWV in Patients with Diabetes and CKD 2249 Table 3. Simple regression analyses of factors that affect regional PWV a Factor hf PWV hc PWV hb PWV fa PWV Age b b b b Male gender c Smoking c SBP b b b b DBP b b b b HDL cholesterol d b d Non-HDL cholesterol Hemoglobin b Presence of diabetes b b b b GFR b c c a Data are simple correlation coefficients (r values) and level of significance. b P c P d P Table 4. Multiple regression analyses of factors that affect regional PWV a Factor hf PWV hc PWV hb PWV fa PWV Age b b b b Male gender b b Smoking SBP b c b d DBP d c b HDL cholesterol Non-HDL cholesterol d Hemoglobin Presence of diabetes b b b c GFR c R b b b b a Data are standard regression coefficients ( values) and level of significance. b P c P d P Aoun et al. (25) reported that aortic PWV correlated with GFR in patients with diabetes (type unspecified), who had a mean GFR of ml/min per 1.73 m 2. They did not examine the association of arterial stiffness with albuminuria. According to Ronnback et al. (26), age-related increase in pulse pressure, a crude index of arterial stiffness, occurred earlier in those with micro- and overt albuminuria in type 1 diabetes, although the effect of GFR on pulse pressure was not described. A recent report by Smith et al. (27) showed that aortic PWV correlated with both albuminuria and GFR in patients with type 2 diabetes and serum creatinine 150 mol/l. However, these associations were NS after adjustment for age, BP, and other confounders. The limitations of these previous studies include the small variation of renal function within each study, so the effect of reduced GFR on arterial stiffness was not detected consistently. Our study enrolled a large number of patients who had type 2 diabetes with and without early and advanced nephropathy and was able to demonstrate clearly the close association of reduced GFR on arterial stiffness independent of other confounders. With respect to the differential stiffening of regional arteries in CKD, Mourad et al. (28) reported that creatinine clearance correlated with aortic PWV and common carotid artery compliance but not with radial artery compliance in untreated patients who had one or more risk factors for CVD. Their observations are very similar to ours made in patients with type 2 diabetes that CKD was most significantly associated with stiffness of the aorta over the other part of arterial tree and that GFR was associated with only PWV of the aorta when other confounding variables were considered. Taken together, these studies indicate that CKD is preferentially associated with stiffening of the central over peripheral arteries, regardless of the presence of diabetes. This study showed that CKD was more strongly associated with stiffness of the aorta than stiffness of other pars of the arterial system. This has a clinical implication, because aortic

6 2250 Journal of the American Society of Nephrology J Am Soc Nephrol 17: , 2006 Table 5. Multiple regression analysis to examine the influence of medications and anemia on hf PWV in patients with diabetes a Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Age b b b b b b Male gender c b c c b b Smoking SBP b b b b b b DBP HDL cholesterol Non-HDL cholesterol d d d d c b GFR d d d d d Use of statins Use of pioglitazone Use of antihypertensives Hemoglobin R b b b b b b a Data are standard regression coefficients ( values) and level of significance. b P c P d P stiffness is a strong and independent predictor of CVD death, as shown in ESRD (6,29), diabetes (30), hypertension (31), and the elderly population (32). A recent study by Pannier et al. (18) showed that PWV of the aorta but not of brachial or femorotibial arteries predicted the mortality risk in patients with ESRD. Pulse pressure is a crude index of arterial stiffness and was shown to be an independent predictor of CVD in dialysis (33) and other populations. In our study, pulse pressure showed the highest correlation with hf PWV among the four regional PWV. Collectively, these data indicate the importance of central arterial stiffness in CVD. It is not fully understood why CKD is more strongly associated with increased stiffness of the aorta than peripheral arteries. However, the accumulation of advanced glycation end products (AGE) in CKD is one explanation. AGE are deposited on aortic extracellular matrices (34), and aortic AGE content correlates with aortic stiffness in human (35) and rat (34). The degree of aortic tissue glycation increases with age in human (36), and the age-related increase in aortic wall stiffness was prevented by treatment with aminoguanidine, an inhibitor of AGE formation (37), in experimental animals. In addition, an AGE cross-link breaker reduced the stiffness of the aorta but not systemic arterial resistance (38). Finally, pentosidine, one of the major AGE, accumulates in plasma of patients with renal failure (39). Therefore, although we do not have data on AGE, these previous studies strongly suggest the possible contribution of AGE to stiffening of the central artery in CKD. It is important to note that, although statistically significant, the contribution of decreased GFR to increased hf PWV was smaller than that of BP, age, or the presence of diabetes when adjusted for these confounding factors. This suggests that the CKD-associated increase in hf PWV is explained to a large extent by these factors. Therefore, knowing GFR may not contribute to the prediction of PWV in patients with diabetes beyond these variables. There are a few limitations to our study. First, this is a cross-sectional study. Therefore, the solid conclusion must await further exploration within the context of outcome studies and attempts at modifying PWV. Second, inclusion of patients with peripheral artery disease might have affected the measurement of PWV of the lower extremities. As we previously showed (22), hemodynamically significant stenosis of peripheral arteries decreases PWV of the arterial segment, because PWV is dependent on pressure. Although we excluded patients with a reduced ABI 0.9 to minimize such an influence, the groups with advanced stages of CKD still may include patients who have peripheral arterial disease with vascular calcification showing normal or even elevated ABI. Third, GFR was estimated indirectly by the use of the MDRD equation. Because age is the common determinant of PWV and the MDRD equation, age might have confounded the observed relationship between GFR and PWV. However, we found that the estimated GFR had a significant association with hf PWV even after adjustment for age and other possible confounders using multivariate models, supporting the conclusion that renal function itself is an important determinant of central arterial stiffness. Further support is a recent study by Briet et al. (14), who directly measured GFR with the use of renal clearance of 51 Cr-EDTA and showed that GFR was inversely associated with elastic properties of carotid artery in 95 patients with CKD. Fourth, some medications might have affected the results because glitazones, statins, and antihypertensive drugs were shown to decrease arterial stiffness in previous studies. It is possible that physicians had avoided some of these drugs for fear of edema, rhabdomyolysis, or hyperkalemia in patients with reduced GFR. Then, the observed association between reduced GFR and increased

7 J Am Soc Nephrol 17: , 2006 Regional PWV in Patients with Diabetes and CKD 2251 PWV might have been confounded by the medications. To avoid such an influence, we included the use of these medications in the multivariate analysis and confirmed that the inverse association between GFR and hf PWV remained significant after such adjustment. Conclusion Our study showed that the degree of CKD-associated increase in arterial stiffness varies among arterial regions in type 2 diabetes. Decreased GFR had the strongest impact on stiffness of the aorta among the four arterial regions, although its independent contribution was smaller than that of elevated BP. Because aortic stiffness is a strong and independent predictor of death from CVD (6,29), this finding could explain the increase in the risk for CVD in predialysis patients with CKD. Further studies are needed to confirm the cross-sectional results in a longitudinal setting and to examine whether these findings in patients with diabetes also are true for patients who have CKD without diabetes. Acknowledgments Part of this study was presented at the 75th European Atherosclerosis Society Congress; Prague, Czech Republic; April 23 to 26, 2005; and published as an abstract (Atherosclerosis 6[Suppl]: 136, 2005). We thank Drs. Teruo Okamoto, Kyoko Izumotani, and Miyoko Komatsu and other staff at the Osaka Municipal Health Promotion Center (Osaka, Japan) for kind assistance in this study. References 1. Lindner A, Charra B, Sherrard DJ, Scribner BH: Accelerated atherosclerosis in prolonged maintenance hemodialysis. 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