Department of Metabolism, Endocrinology and Molecular Medicine, Osaka City University Graduate School of Medicine, Osaka, Japan
Adddress 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 545-8585, Japan. Phone: +81-6-6645-3806; Fax: +81-6-6645-3808; E-mail: t-shoji{at}med.osaka-cu.ac.jp
Received for publication October 7, 2005.
Accepted for publication May 29, 2006.
Increased arterial stiffness is an independent predictor ofdeath from cardiovascular disease, and aortic stiffness is morepredictive than stiffness of other arterial regions. Becauselittle is known about the effect of chronic kidney disease (CKD)on regional arterial stiffness, pulse wave velocity (PWV) offour different arterial segments was measured in patients whohad type 2 diabetes with and without various stages of CKD.A total of 434 patients had type 2 diabetes, and there were192 healthy control subjects who were comparable in age andgender. GFR was estimated by the abbreviated Modification ofDiet in Renal Disease equation. The patients with diabetes wereclassified into CKD stages by the definition of the Kidney DiseaseOutcomes Quality Initiative guidelines. PWV was measured inthe heart-femoral, heart-carotid, heart-brachial, and femoral-anklesegments simultaneously using an automatic pulse wave analyzer.PWV of each arterial region was increased in patients who haddiabetes without kidney damage and was increased further ina stepwise manner with the advanced stages of CKD. The increasein PWV was greater in the heart-femoral and heart-carotid regionsthan in the heart-brachial and femoral-ankle segments. However,after adjustment for age, BP, and other confounding factorsusing a multiple regression model, decreased GFR was independentlyassociated with increased PWV of the heart-femoral region butnot with PWV of other arterial segments. In type 2 diabetes,CKD was associated with increased stiffness of arteries, particularlyof the aorta. The cross-sectional result may explain the increasedrisk for cardiovascular disease in CKD, although longitudinalstudies are needed to confirm it.
Hemodialysis patients are at an increased risk for death fromcardiovascular disease (CVD) (1–3), and those with diabeteshave a further elevated risk for CVD (4). The poorer prognosisin hemodialysis patients with diabetes are explained, at leastpartly, by the more advanced thickening (5) and stiffening (6)of large arteries. In fact, these vascular changes are significantand independent predictors for CVD mortality in hemodialysispopulations (6,7). A recent study (8) showed that the CVD riskincreases in a stepwise manner as GFR declines. We showed thatpredialysis patients with advanced stages of chronic kidneydisease (CKD) have increased arterial thickness (9,10) and stiffness(11). Recent studies (12–14) revealed a stepwise increasein arterial stiffness as a function of decreased GFR or thestages of CKD. CKD itself, rather than hemodialysis, is a strongrisk 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 (elastic)arteries and smaller peripheral (muscular) arteries. The formerrepresents the principal capacitive system, whereas the latterplays a major role in conduit function (15). London et al. (16)reported that the increase in arterial stiffness among hemodialysispatients was more significant for the central than the peripheralarteries. We recently showed that patients who have type 2 diabetesbut without renal complications have preferential stiffeningin central over peripheral arteries by measuring pulse wavevelocity (PWV) in different regions of the arterial tree (17).In the same study, aging was associated with increased stiffnessof 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 differentpower in predicting CVD death, as recently shown in hemodialysispatients (18). So far, however, no study has examined the effectof decreased GFR or stages of CKD on regional arterial stiffness.In this study, we evaluated the effects of CKD on regional arterialstiffness by measuring PWV of four different arterial segmentsin patients with type 2 diabetes and various stages of CKD.
Patients
A total of 434 patients had type 2 diabetes, and there were192 healthy control subjects. They gave informed consent toparticipate in the study.
CKD was defined as either kidney damage or GFR <60 ml/minper 1.73 m2 according to the Kidney Disease Outcomes QualityInitiative Clinical Practice Guidelines (19). Increased urinaryalbumin/creatinine ratio >30 mg/g was used as evidence ofkidney damage (20). The GFR was calculated by the abbreviatedversion of the Modification of Diet in Renal Disease (MDRD)study equation (19) GFR (ml/min per 1.73 m2) = 186 x SCr–1.154x age–0.203 x 0.742 (if female), where SCr is serum creatinineconcentration in mg/dl.
Diagnosis of diabetes was made according to the American DiabetesAssociation criteria (21). We excluded those who had type 1diabetes and were positive for GAD antibody, had a history ofketoacidosis, or were dependent on insulin therapy for survival.Gestational diabetes and diabetes associated with specific syndromewere carefully ruled out by their history.
The healthy control subjects were screened from participantsof a local health check program in Osaka City. Exclusion criteriawere fasting plasma glucose level >7.0 mmol/L (126 mg/dl);kidney damage defined as urinary albumin/creatinine ratio >30mg/g and/or decreased estimated GFR <60 ml/min per 1.73 m2;liver dysfunction defined as AST >50 IU/L; current medicationfor diabetes, hypertension, and/or dyslipidemia; and historyof myocardial infarction and/or cerebral infarction. Becausehemodynamically significant stenosis of leg arteries affectsPWV of the lower extremities (22), we excluded those who hadreduced ankle-brachial pressure index (ABI) <0.9 from thetotal participants.
PWV and BP Measurement
PWV and BP were measured in the supine position after 5 minof bed rest using an automatic waveform analyzer (model BP-203RPE;Colin, Komaki, Japan) as described previously (17). Pressurewaveforms of the brachial and tibial arteries were recordedby an oscillometric method using the occlusion/sensing cuffsadapted to both arms and both ankles. Pressure waveforms ofthe carotid and femoral arteries were recorded using multielementtonometry sensors placed at the left carotid and the left femoralarteries. Electrocardiogram was monitored with electrodes placedon both wrists. Heart sounds S1 and S2 were detected by a microphoneset on the left edge of the sternum at the third intercostalspace.
The waveform analyzer measures time intervals between S2 andthe notch of carotid pulse wave (Thc), between S2 and the notchof brachial pulse wave (Thb), between pulse waves of the carotidand femoral arteries (Tcf), and between pulse waves of the femoraland tibial (ankle) arteries (Tfa). The sum of Thc and Tcf givesthe time for pulse waves to travel form the heart (aortic orifice)to the femoral artery (Thf). Also, the waveform analyzer estimatesthe 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 followingformulas: Dhc = 0.2437 x HT – 18.999; Dhb = 0.2195 x HT– 2.0734; Dhf = 0.5643 x HT – 18.381; and Dfa =0.2486 x HT + 30.709. PWV was calculated for each arterial segmentas the path length divided by the corresponding time interval.
This method allowed us to perform simultaneous and automatedmeasurements of PWV for the four arterial segments. This isa great advantage over other methods that require manual andconsecutive measurements of pulse wave transit times from onesite to another. Reproducibility of the automated PWV measurementwas 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 faPWV, respectively, when evaluated by repeating measurementsin 17 healthy subjects on two different occasions.
Blood Sampling and Measurements
Blood was drawn in the morning after an overnight fast for atleast 12 h. Serum creatinine was measured by an enzymatic method.Hemoglobin A1c was measured by HPLC, and plasma glucose wasmeasured by a glucose oxidase method. Other measurements weredone by routine laboratory methods.
Statistical Analyses
Results were summarized as mean ± SE. One-way ANOVA wasused to assess the difference in mean values between groups,and then a post hoc test was performed by Scheffe-type multiplecomparison test. Two-way ANOVA was used to evaluate effectsof two categorical variables on one continuous variable. Thedifference in prevalence was assessed by 2 test. The correlationbetween two variables was examined by linear regression analysis.Independent association between the variables was assessed bymultiple regression analysis. P < 0.05 was taken as statisticallysignificant. All calculations were performed by a personal computerusing statistics software (Statview5 for Windows; SAS InstituteInc., Cary, NC).
Characteristics of Participants Table 1 summarizes the characteristics of the six groups ofparticipants. These groups were comparable in age and gender.Parameters of glycemia and renal function were significantlydifferent by definition. Also, there was significant differencein BP; plasma lipids; smoking habit; and the use of medicationsfor 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 patientswho had diabetes without CKD had significantly increased hfPWV (Figure 1, top), and it was increased further as the CKDstages were advanced. The same was true for hc PWV, hb PWV andfa PWV. When the healthy subjects were excluded, the effectof CKD stages on PWV within the patients with diabetes againwas significant for hf PWV, hc PWV and hb PWV but not for faPWV (data not shown).
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. aP < 0.05 versus the healthy controls; bP < 0.05 versus DMnonCKD; cP < 0.05 versus DMCKD1 by Scheffe-type multiple comparison. Mean ± SE. (Bottom) Correlation between GFR and hf PWV. , healthy subjects; •, patients with diabetes; DMnonCKD, patients who have diabetes without CKD; DMCKD1–5, patients who have diabetes and CKD stages 1 through 5, respectively.
Different Influence of CKD on Regional PWV
Because absolute values of PWV were different among the foursegments of artery, it was difficult to compare directly theeffect of CKD on PWV in different arterial regions. Blacheret al. (23) calculated a PWV index (difference between actualPWV from the theoretical PWV predicted by age, gender, BP, andpulse rate) for carotid-femoral PWV. However, it still was inappropriatefor comparison of PWV among different arterial segments. Then,we expressed regional PWV values of each patient with diabetesas percentages relative to the corresponding mean PWV valueof the healthy subjects, and the standardized PWV values werecompared among the patients with diabetes in different stagesof CKD (Figure 2). The effect of CKD stages and the effect ofarterial regions on the standardized PWV both were significantby two-way ANOVA, but the effect of CKD stages was significantlydifferent among the four regions as indicated by the presenceof significant interaction between the effects of CKD stagesand arterial regions. Thus, the magnitude of the influence ofCKD 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.
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, femoral-ankle.
Simple Regression Analysis of Factors Affecting Regional PWV
Factors that correlated with PWV in the four arterial segmentsin all participants were examined by simple regression analysis(Table 3). A reduced GFR correlated significantly with increasedPWV 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 associatedwith increased PWV of the four arterial regions.
Table 3. Simple regression analyses of factors that affect regional PWVa
Multiple Regression Analysis of Factors Affecting Regional PWV
Multiple regression analysis was performed to examine whetherreduced GFR was an independent factor that affected regionalPWV in all participants (Table 4). After adjustment for age,gender, smoking, BP, lipids, and the presence of diabetes, reducedGFR was significantly associated with increased PWV of the heart-femoralsegment but not with PWV of other arterial regions. Age andsystolic BP were significant factors associated with increasedPWV in the four arterial segments. The effect of the presenceof diabetes on PWV was significant in the four arterial segmentsstudied. Non–HDL cholesterol was the significant factorassociated with hf PWV. These models explained 24.3 to 54.7%of variance in regional PWV of the four arterial segments (Table 4).
Table 4. Multiple regression analyses of factors that affect regional PWVa
To examine possible influences of medications and anemia onthe inverse association between GFR and hf PWV, we performedfurther analyses using multiple regression models in the patientswith diabetes (Table 5). The first model showed that the associationbetween GFR and hf PWV was significant when the effects of medicationswere not considered. Then, the use of statins (model 2), pioglitazone(model 3), or antihypertensives (model 4) was added as anothercovariate, but none of these covariates or the combination ofthem (model 5) had significant association with hf PWV. Whencalcium channel blockers, angiotensin-converting enzyme inhibitors,and angiotensin II receptor blockers were analyzed separately,no significant association was found independent of BP and otherfactors (data not shown). Even after these adjustments, theinverse association between GFR and hf PWV remained significant.In the final model (model 6) to which the level of hemoglobinwas added further as the 12th covariate, hemoglobin was nota significant factor in the model. Also, the association ofGFR with hf PWV was no longer significant.
Table 5. Multiple regression analysis to examine the influence of medications and anemia on hf PWV in patients with diabetesa
Correlation of Pulse Pressure with Regional PWV
Because pulse pressure is a crude index of arterial stiffness,we calculated correlation coefficients between pulse pressureand each regional PWV in all participants. It was 0.545, 0.273,0.481, and 0.288 (P < 0.001 for all) for hf PWV, hc PWV,hb PWV, and fa PWV, respectively.
Patients who are on hemodialysis are at a very high risk fordeath from CVD. A recent study (8) revealed that predialysispatients with CKD show a stepwise increase in the risk for CVD.Our study showed in patients with type 2 diabetes that arterialstiffness as measured by PWV was higher in those with more advancedstages of CKD. More important, we showed for the first timethat there was a significant regional difference in the degreeof arterial stiffening associated with CKD and that a reducedGFR had the strongest impact on PWV of the aorta among the fourarterial regions studied.
There are only a few studies on arterial stiffness in patientswith diabetes and CKD. We (24) previously found in patientswho had type 2 diabetes with and without microalbuminuria thatthe stiffness of the carotid artery was associated with GFRbut not with albuminuria, independent of other clinical factors.Aoun et al. (25) reported that aortic PWV correlated with GFRin patients with diabetes (type unspecified), who had a meanGFR of 81 ± 24 ml/min per 1.73 m2. They did not examinethe association of arterial stiffness with albuminuria. Accordingto Ronnback et al. (26), age-related increase in pulse pressure,a crude index of arterial stiffness, occurred earlier in thosewith micro- and overt albuminuria in type 1 diabetes, althoughthe effect of GFR on pulse pressure was not described. A recentreport by Smith et al. (27) showed that aortic PWV correlatedwith both albuminuria and GFR in patients with type 2 diabetesand serum creatinine <150 µmol/L. However, these associationswere NS after adjustment for age, BP, and other confounders.The limitations of these previous studies include the smallvariation of renal function within each study, so the effectof reduced GFR on arterial stiffness was not detected consistently.Our study enrolled a large number of patients who had type 2diabetes with and without early and advanced nephropathy andwas able to demonstrate clearly the close association of reducedGFR on arterial stiffness independent of other confounders.
With respect to the differential stiffening of regional arteriesin CKD, Mourad et al. (28) reported that creatinine clearancecorrelated with aortic PWV and common carotid artery compliancebut not with radial artery compliance in untreated patientswho had one or more risk factors for CVD. Their observationsare very similar to ours made in patients with type 2 diabetesthat CKD was most significantly associated with stiffness ofthe aorta over the other part of arterial tree and that GFRwas associated with only PWV of the aorta when other confoundingvariables were considered. Taken together, these studies indicatethat CKD is preferentially associated with stiffening of thecentral over peripheral arteries, regardless of the presenceof diabetes.
This study showed that CKD was more strongly associated withstiffness of the aorta than stiffness of other pars of the arterialsystem. This has a clinical implication, because aortic stiffnessis a strong and independent predictor of CVD death, as shownin ESRD (6,29), diabetes (30), hypertension (31), and the elderlypopulation (32). A recent study by Pannier et al. (18) showedthat PWV of the aorta but not of brachial or femorotibial arteriespredicted the mortality risk in patients with ESRD. Pulse pressureis a crude index of arterial stiffness and was shown to be anindependent predictor of CVD in dialysis (33) and other populations.In our study, pulse pressure showed the highest correlationwith hf PWV among the four regional PWV. Collectively, thesedata indicate the importance of central arterial stiffness inCVD.
It is not fully understood why CKD is more strongly associatedwith 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 aorticextracellular matrices (34), and aortic AGE content correlateswith aortic stiffness in human (35) and rat (34). The degreeof aortic tissue glycation increases with age in human (36),and the age-related increase in aortic wall stiffness was preventedby treatment with aminoguanidine, an inhibitor of AGE formation(37), in experimental animals. In addition, an AGE cross-linkbreaker reduced the stiffness of the aorta but not systemicarterial resistance (38). Finally, pentosidine, one of the majorAGE, accumulates in plasma of patients with renal failure (39).Therefore, although we do not have data on AGE, these previousstudies strongly suggest the possible contribution of AGE tostiffening 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 smallerthan that of BP, age, or the presence of diabetes when adjustedfor these confounding factors. This suggests that the CKD-associatedincrease in hf PWV is explained to a large extent by these factors.Therefore, knowing GFR may not contribute to the predictionof PWV in patients with diabetes beyond these variables.
There are a few limitations to our study. First, this is a cross-sectionalstudy. Therefore, the solid conclusion must await further explorationwithin the context of outcome studies and attempts at modifyingPWV. Second, inclusion of patients with peripheral artery diseasemight have affected the measurement of PWV of the lower extremities.As we previously showed (22), hemodynamically significant stenosisof peripheral arteries decreases PWV of the arterial segment,because PWV is dependent on pressure. Although we excluded patientswith a reduced ABI <0.9 to minimize such an influence, thegroups with advanced stages of CKD still may include patientswho have peripheral arterial disease with vascular calcificationshowing normal or even elevated ABI. Third, GFR was estimatedindirectly by the use of the MDRD equation. Because age is thecommon determinant of PWV and the MDRD equation, age might haveconfounded the observed relationship between GFR and PWV. However,we found that the estimated GFR had a significant associationwith hf PWV even after adjustment for age and other possibleconfounders using multivariate models, supporting the conclusionthat renal function itself is an important determinant of centralarterial stiffness. Further support is a recent study by Brietet al. (14), who directly measured GFR with the use of renalclearance of 51Cr-EDTA and showed that GFR was inversely associatedwith elastic properties of carotid artery in 95 patients withCKD. Fourth, some medications might have affected the resultsbecause glitazones, statins, and antihypertensive drugs wereshown to decrease arterial stiffness in previous studies. Itis possible that physicians had avoided some of these drugsfor fear of edema, rhabdomyolysis, or hyperkalemia in patientswith reduced GFR. Then, the observed association between reducedGFR and increased PWV might have been confounded by the medications.To avoid such an influence, we included the use of these medicationsin the multivariate analysis and confirmed that the inverseassociation between GFR and hf PWV remained significant aftersuch adjustment.
Our study showed that the degree of CKD-associated increasein arterial stiffness varies among arterial regions in type2 diabetes. Decreased GFR had the strongest impact on stiffnessof the aorta among the four arterial regions, although its independentcontribution was smaller than that of elevated BP. Because aorticstiffness is a strong and independent predictor of death fromCVD (6,29), this finding could explain the increase in the riskfor CVD in predialysis patients with CKD. Further studies areneeded to confirm the cross-sectional results in a longitudinalsetting and to examine whether these findings in patients withdiabetes also are true for patients who have CKD without diabetes.
Acknowledgments
Part of this study was presented at the 75th European AtherosclerosisSociety 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 Komatsuand other staff at the Osaka Municipal Health Promotion Center(Osaka, Japan) for kind assistance in this study.
Footnotes
Published online ahead of print. Publication date availableat www.jasn.org.
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Top
Abstract
Introduction
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). 
, healthy subjects; •, patients with diabetes; DMnonCKD, patients who have diabetes without CKD; DMCKD1–5, patients who have diabetes and CKD stages 1 through 5, respectively.