Association between Urine Creatinine Excretion and Arterial Stiffness in Chronic Kidney Disease: Data from the KNOW-CKD Study Open Access

Muscle wasting is prevalent in patients with chronic kidney disease (CKD), regardless of dependency on dialysis [1,2]. Low muscle mass is clinically important in this group because of its relation to poor physical performance [3], cognitive dysfunction [4], and poor survival [5,6], although the underlying mechanism is not well known.

Arterial stiffness measured by pulse wave velocity (PWV) predicts cardiovascular events, including cardiovascular and all-cause mortality in the general population and in different groups with comorbidities, such as hypertension, diabetes and CKD [7,8]. It is well-known that arterial stiffness increases as estimated glomerular filtration rate (eGFR) declines [9], and cardiovascular diseases are major causes of death in CKD. These findings suggest the role of arterial stiffness as a link between low muscle mass and poor cardiovascular outcomes in CKD. The relationship between muscle mass and arterial stiffness in CKD is not well known, although previous studies have found an association in non-CKD populations [10,11,12].

Creatinine is a metabolite of creatine in muscle. It is produced at a constant rate according to muscle mass. Therefore, urinary creatinine excretion is used to assess both the completeness of 24-hr urine collection and the body's muscle mass [13]. Previous studies have found that UCr is well correlated with lean body mass in non-CKD and CKD populations in a steady state [14,15]. The aim of this study was to investigate the association between muscle mass and arterial stiffness through the measurement of creatinine excretion and PWV in a Korean CKD cohort.

This is a cross-sectional study designed to examine the association between 24-hr urinary creatinine excretion (UCr) and PWV in CKD patients. Study subjects were participants in the prospective Korean Cohort Study for Outcome in Patients With Chronic Kidney Disease (KNOW-CKD). A detailed protocol of this study has been published previously [16]. The study protocol was approved by the IRB at each participating clinical center in 2011. In brief, KNOW-CKD is a prospective cohort study that enrolls subjects with predialysis CKD stages 1 to 5 and who are between the ages of 20 years and 75 years. Nine nephrology centers in major university hospitals throughout Korea enrolled approximately 2,450 adults with chronic kidney disease over a 5-year period from 2011 to 2015. The participating individuals will be monitored for approximately 10 years until death or until end-stage renal disease occurs. Between 2011 and 2013, 1,529 CKD patients were enrolled in the KNOW-CKD study. We analyzed 1,017 participants from this cohort who underwent a 24-hr urine collection and brachial-ankle PWV (baPWV) at baseline examination. We excluded 625 participants who were missing data for the variables of interest and 16 participants with a history of peripheral arterial disease. The final analysis included 888 participants.

Data regarding socio-demographic information, medical history, medication use, and health-related behaviors were collected through a self-administered questionnaire, with the assistance of trained staff. Anthropometric data and resting blood pressure (BP) were measured by trained nurses. Blood samples were taken after fasting for at least 10 hours. Random urine samples from midstream collection were used to measure the urine albumin-to-creatinine ratio (ACR). Serum creatinine and 25-(OH)-vit D and random urine albumin and creatinine were measured at the central laboratory. Other biochemical analyses were done at the local laboratory of each participating center. Serum creatinine levels were measured by the isotope dilution mass spectroscopy (IDMS)-traceable method. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [17] as follows: eGFR = 141 × min (serum creatinine/κ,1)^α × max (serum creatinine/κ,1)^-1.209 × 0.993^age × 1.018 (if female) × 1.159 (if black), where κ = 0.7 for females and 0.9 for males, α = -0.329 for females and -0.411 for males, min indicates the minimum of serum creatinine/κ or 1, and max indicates the maximum of serum creatinine/κ or 1. A 24-hr urine specimen was collected as routine recommendation, and 24-hr urine creatinine excretion was measured. Urine collection began after emptying the bladder in the morning and continued for the next 24 hours, including the last urination the next morning. Both the right and left baPWV were measured according to the protocol of each participating center, and we used the mean of the right and left baPWV in the analysis. Hypertension was defined as a systolic blood pressure > 140 mmHg, diastolic blood pressure > 90 mmHg, or a history of hypertension. Diabetes mellitus was defined as a fasting serum glucose > 126 mg/dL or a history of diabetes.

Participants were divided into four groups according to the quartiles of UCr. Continuous variables were expressed as the mean ± standard deviation or median (interquartile range). Continuous variables were compared between two groups with a t-test or the Mann-Whitney U test, and continuous variables were compared between the four groups with analysis of variance or the Kruskal-Wallis test. Categorical variables were expressed as percentages and compared between groups with the χ² test. Multivariate linear regression analysis was used to evaluate the potential association between the absolute value of baPWV and UCr. The subjects were classified into two groups with normal baPWV and high baPWV. High baPWV was defined as the highest quintile of baPWV. Logistic regression analysis was used to determine the OR (odds ratio) and CI (confidence interval) for the presence of high baPWV associated with different UCr quartiles compared to the highest quartile group. Statistical analyses were performed with Stata Version 13 (StataCorp LP, College Station, TX, USA).

The baseline characteristics of study participants classified by UCr quartile are summarized in Table 1. The baPWV, age, and intact PTH were highest in the 1st quartile of UCr and lowest in the 4th quartile. In contrast, male participants, BMI, waist circumference, eGFR, and 25-(OH)-vitamin D were lowest in the 1st quartile of UCr and highest in the 4th quartile.

Overall, 177 (19.9%) participants had high baPWV and 711 (80.1%) had normal baPWV. The characteristics of participants with high baPWV were compared to those with normal baPWV. Participants with high baPWV had lower UCr (1020.3±361.3 cm/s) than those with normal baPWV (1207.8±418.4 cm/s, P<0.001), suggesting an inverse relationship between baPWV and UCr (Figure 1). As expected, participants with baPWV had worse profiles in terms of cardiovascular risks. They had higher age, systolic BP, waist circumference, glucose, hsCRP, ACR, alkaline phosphatase (AP), and intact parathyroid hormone (PTH), and lower hemoglobin and eGFR. However, more participants with high baPWV were taking statins (data not shown).

Table 2 summarizes the results of multivariate linear regression analysis of the association between UCr and baPWV. After adjustment for traditional and renal cardiovascular risk factors, the association between high UCr and baPWV remained significant. For each 100 mg/d increase in UCr, the PWV decreased by 6m/sec in fully adjusted model 3. Similarly, low UCr levels were significantly associated with high baPWV after adjustment for traditional and renal cardiovascular risk factors in multivariate logistic analysis. As shown in Table 3, the OR for high baPWV in the 1st quartile of UCr compared to the 4th quartile was 2.62 (95% CI, 1.24-5.54; P=0.011) in fully adjusted model 3.

In this study, low muscle mass estimated by UCr was associated with increased baPWV in a Korean cohort of CKD patients. This relationship was significant even after multivariate adjustment for both traditional and CKD-related cardiovascular risk factors, and in both linear and logistic regression models.

This finding is consistent with the results of previous studies that have shown an association between decreased muscle mass and arterial stiffness in non-CKD populations. These studies used different methods to assess skeletal muscle mass in the body and arterial stiffness. In a study of 496 middle-aged to elderly Japanese, the mid-thigh muscle cross-sectional area measured by computed tomography (CT) was negatively associated with baPWV in men [12]. Loenneke et al measured mid-thigh muscle cross-sectional area with CT in 27 subjects without cardio-metabolic diseases and found that low muscle mass was inversely associated with the augmentation index [18]. Although CT and MRI are considered the gold standard methods for measuring muscle mass, dual-energy X-ray absorptiometry (DEXA) is a practical alternative for research and clinical use [3]. In a large study of 1,488 Japanese, sarcopenia evaluated by DEXA was associated with greater baPWV in women [19]. Kim et al measured appendicular skeletal muscle mass with DEXA and visceral fat area with CT in 526 healthy Korean adults [11]. In their study, the muscle-to-fat ratio was inversely associated with baPWV. Bioimpedance analysis (BIA) is also a useful tool for measuring body composition without radiation exposure. In a study of 427 elderly Koreans, limb muscle mass measured by BIA was inversely associated with the radial augmentation index in men [20]. Sampaio et al also found an association between a low skeletal muscle mass index by BIA and a cardio-ankle vascular index in community-dwelling older adults [21]. Only a few studies have assessed the relationship between muscle mass and arterial stiffness in CKD patients, and those studies have only considered patients on hemodialysis (HD). In a study of 161 HD patients, the thigh muscle area standardized for the femoral shaft area was measured on CT and showed an inverse association with baPWV [22]. However, the study was done in a relatively small number of patients at a single center. Another prospective interventional study suggests the role of arterial stiffness: Three months of exercise training during dialysis in 19 HD patients improved aortic PWV and increased skeletal muscle mass [23].

There are several explanations for the relationship between muscle mass and arterial stiffness. First, exercise or physical activity might mediate the relationship between muscle mass and arterial stiffness. Indeed, one of the interventional studies described above found that both muscle mass and arterial stiffness are affected by exercise [23]. Second, systemic inflammation is related to both muscle loss and arterial stiffness. For example, inflammatory marker, interleukin-6, and C-reactive protein predict the future loss of total appendicular skeletal muscle in free-living older men and women [24], while the relationship between inflammation and arterial stiffness is well known [25]. Third, insulin resistance may also mediate the relationship between decreased muscle mass and arterial stiffness. Insulin resistance contributes to muscle wasting [26] and is linked to cardiovascular diseases by increased arterial stiffness [27]. Fourth, decreased arterial compliance may lower blood perfusion to the limb muscles, and the resulting muscle atrophy might explain the association [20]. Finally, non-traditional, CKD-related cardiovascular risk factors might contribute to both muscle wasting and arterial stiffness. It is well known that both muscle wasting and arterial stiffness are prevalent in CKD. Previous studies have shown that PTH, vitamin D, and acidosis are associated with arterial stiffness, as well [28,29,30].

This study had several limitations. First, the study had a cross-sectional design, so we could not confirm a causal relationship between low muscle mass and arterial stiffness. Second, some information that might be valuable in this analysis, such as physical activity or markers of insulin resistance, was not available. Lastly, UCr is an indirect measure of muscle mass and could have been affected by diet, drugs, renal function, or errors during collection in our study. However, using UCr to evaluate muscle mass has advantages because it is a simple and inexpensive procedure that most CKD patients undergo in the evaluation of CKD. The relatively large number of study subjects from different centers is another strength of this study. To our knowledge, this is the first study to show an association between low muscle mass and arterial stiffness in predialysis CKD patients.

Low UCr is associated with high baPWV in Korean patients with CKD. Further studies are needed to verify the causal relationship between UCR and baPWV and the role of muscle mass in the development of cardiovascular disease in CKD.

All the authors declared no conflict of interest and nothing to disclose.

This work was supported by the Research Program funded by the Korea Centers for Disease Control and Prevention (2011E3300300, 2012E3301100, 2013E3301600).