Journal of Renal Nutrition
Volume 19, Issue 5 , Pages 357-364, September 2009

Relationship Between Adiposity and Cardiovascular Risk Factors in Prevalent Hemodialysis Patients

  • George A. Kaysen, MD, PhD, FASN

      Affiliations

    • Renal Research Institute, New York, New York
    • Division of Nephrology, Department of Medicine and Department of Biochemistry and Molecular Medicine, University of California at Davis, Davis, California
    • Research Service, Veterans Administration Northern California Health Care System, Mather, California
    • Corresponding Author InformationAddress reprint requests to George A. Kaysen, MD, PhD, FASN, Division of Nephrology, Department of Medicine, University of California at Davis, One Shields Ave., Genome and Biomedical Sciences Facility 451 Health Sciences Dr., Davis, CA 95616.
    • ,
  • Peter Kotanko

      Affiliations

    • Renal Research Institute, New York, New York
    • Krankenhaus der Barmherzigen Brueder, Graz, Austria
    • ,
  • Fansan Zhu, MS

      Affiliations

    • Renal Research Institute, New York, New York
    • ,
  • Shubho R. Sarkar, MD, FASN

      Affiliations

    • Renal Research Institute, New York, New York
    • Department of Medicine, Weil Cornell Medical Center, New York, New York
    • ,
  • Steven B. Heymsfield, MD

      Affiliations

    • Department of Internal Medicine, New York Obesity Research Center, St. Luke's Hospital, New York, New York
    • ,
  • Martin K. Kuhlmann, MD

      Affiliations

    • Renal Research Institute, New York, New York
    • ,
  • Tjien Dwyer

      Affiliations

    • Division of Nephrology, Department of Medicine and Department of Biochemistry and Molecular Medicine, University of California at Davis, Davis, California
    • ,
  • Len Usvyat, MCP

      Affiliations

    • Renal Research Institute, New York, New York
    • ,
  • Peter Havel, DVM, PhD

      Affiliations

    • Department of Molecular Biosciences, School of Veterinary Medicine, and Department of Nutrition, University of California at Davis, Davis, California
    • ,
  • Nathan W. Levin, MD, FASN

      Affiliations

    • Renal Research Institute, New York, New York

published online 13 July 2009.

Article Outline

Objective

Increased body mass index (BMI) is associated with reduced all-cause and cardiovascular (CV) mortality in hemodialysis (HD) patients, whereas CV risk increases with BMI in the general population. In the general population, obesity is associated with inflammation, decreased high-density lipoprotein (HDL) cholesterol, increased low-density lipoprotein (LDL) cholesterol, and triglycerides (TGs), all risk factors for CV disease. Low-density lipoprotein cholesterol does not predict CV risk in HD, whereas increased C-reactive protein and interleukin-6 (IL-6), low HDL and apolipoprotein (apo) AI, and increased fasting TGs do predict risk. Renal failure is associated with dyslipidemia and inflammation in normal-weight patients. We hypothesized that the effects of obesity may be obscured by renal failure in HD.

Methods

We explored the relationship between adipose tissue pools and distribution, i.e., subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) (measured by magnetic resonance imaging) and measures of inflammation (C-reactive protein, IL-6, ceruloplasmin, and α1 acid glycoprotein), HDL and LDL cholesterol, total TGs, apo AI, apo B, apo CII (an activator of lipoprotein lipase), apo CIII (an inhibitor of lipoprotein lipase), and the adipokines, leptin and adiponectin, in 48 patients with prevalent HD.

Results and Conclusions

Total TG concentrations were positively correlated with VAT controlled for age, sex, and weight. Both apo CII and apo CIII were correlated only with VAT. Adiponectin was inversely correlated with VAT, and leptin was positively associated with SAT. C-reactive protein and α1 acid glycoprotein were weakly associated with SAT, whereas ceruloplasmin was strongly associated with VAT according to multiple regression analysis. In contrast, apo B, LDL, apo AI, HDL, and IL-6 were not correlated with any measure of body composition, potentially mitigating the effects of obesity in HD.

 

ALTHOUGH THE RELATIVE risk of mortality is high among dialysis patients, one factor that predicts survival is a higher body mass index (BMI).1, 2, 3 Body mass index is imprecise as a measure of body composition, and does not distinguish between muscle and fat mass. Nevertheless, the lack of an increase in mortality among a population with a very high BMI (>35kg/m2) strongly supports the hypothesis that adiposity in some way protects dialysis patients from mortality, or that risk factors normally associated with adiposity may not be associated with adiposity among dialysis patients. Indices associated with lean body mass, such as total body water, approximated by the volume of distribution of urea, independently predict survival.4, 5 Similarly, total body potassium, a measure of intracellular volume, predicts survival in a variety of chronic diseases.6, 7, 8 Although the positive association between lean body mass and survival can be explained by better-preserved nutritional reserves or lower comorbidities, the basis for improved survival among obese patients is not obvious, although a similar survival advantage is evident in patients with other chronic diseases.9

Several cardiovascular risk factors are linked metabolically to body composition among subjects with normal kidney function.10 Low-density lipoprotein (LDL) cholesterol levels and triglyceride (TG) levels are positively associated with adiposity, whereas high-density lipoprotein (HDL) cholesterol is inversely associated with adiposity among subjects with normal kidney function.11 Inflammation, as assessed by plasma C-reactive protein (CRP) or interleukin-6 (IL-6) concentrations, is also an important cardiovascular risk factor, both in dialysis patients and in subjects with normal kidney function.12, 13, 14 C-reactive protein and IL-6 levels are thought to be associated with adiposity in subjects with normal kidney function as a result of inflammation within or caused by increased visceral adipose mass.15, 16 A third set of risk factors associated with adiposity both in the population with normal kidney function and in patients with kidney failure consists of the adipokines, leptin and adiponectin.

Although some risk factors that predict cardiovascular disease among populations without kidney failure are no longer predictive in dialysis patients, such as hypertension and LDL cholesterol,17 other risk factors preserve their predictive values, such as CRP, IL-6,12, 13, 18 and low levels of HDL cholesterol.17, 19

Elevated TGs are also associated with mortality among dialysis patients.19 Although TG levels are associated with adiposity among subjects with normal kidney function, TG levels are also increased in dialysis patients by factors that may not be linked to body composition, such as increased levels of lipoprotein lipase inhibitors such as apolipoprotein CIII (apo CIII),20, 21 which is also linked to insulin resistance and increased body adiposity.

A third cluster of risk factors associated with body composition modulating cardiovascular risk consists of the adipokines.22, 23 Leptin is secreted by adipocytes, and is increased in dialysis patients beyond what would be anticipated by total fat mass, primarily because of a reduced renal clearance of leptin,24, 25 although the relationship to adiposity persists within populations of patients with renal failure.24, 25 Leptin is associated with insulin resistance, and increased circulating leptin was directly associated with vascular disease.26, 27, 28, 29 Circulating concentrations of a second adipokine, adiponectin, are inversely proportion to fat mass,30 and specifically, are inversely related to the important visceral adipose tissue mass.31, 32 Adiponectin, like HDL, was reported to be inversely associated with vascular disease in subjects with normal renal function.33 The relationship between adiponectin levels and cardiovascular risk in patients with kidney disease is controversial. High levels were associated with increased cardiovascular risk in some studies of dialysis patients,23 and in patients with stage 3 and 4 chronic kidney disease,34 whereas high levels were reported to be protective in other studies.22

In the present study, we measured body adipose tissue compartments and lean body mass, using magnetic resonance imaging (MRI), in a cohort of HD patients, to investigate the relationship between adiposity and a number of risk factors for cardiovascular disease.

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Methods 

Institutional Review Board approval was obtained, and all subjects gave written, informed consent before participation. Forty-eight prevalent HD patients (20 women and 28 men, aged >18 years) were chosen, to encompass a wide range of BMIs and ages. Thirty-seven patients were African American, 3 were nonblack Hispanic, 3 were white, 2 were Asian, and 3 were “other.” Sixteen patients had diabetes mellitus. For an analysis of the effects of race, patients were coded as black or nonblack because of the small numbers in the other groups. All but one subject had been on maintenance HD for at least 3 months before the study. One subject had been on dialysis for 2 months. They were studied on the day of a regularly scheduled HD session, approximately 3hours before initiation of a dialysis treatment.

After an overnight fast, body weight was measured to the nearest 0.1kg (Weight Tronix, New York, NY), and height was measured to the nearest 0.5cm using a stadiometer (Holtain, Crosswell, UK). Whole-body MRI scans were prepared using a 1.5-Tesla scanner (6X Horizon, General Electric, Milwaukee, WI) to evaluate muscle and fat mass.35

All assays were performed on serum obtained while the patient was in a fasting state. The inflammatory markers CRP and IL-6, the long-lived acute-phase proteins ceruloplasmin and α1 acid glycoprotein, the adipokines leptin and adiponectin, apo AI, apo CII, apo CIII, apo B, TGs, total cholesterol, HDL cholesterol, and LDL cholesterol were measured. C-reactive protein, ceruloplasmin, apo AI, apo B, and α1 acid glycoprotein were measured by rate nephelometry, using a Beckman Array (Beckman, Ramsey, MN) automated nephelometer.36 We measured apo CII and apo CIII nephelometrically, using a Hitachi chemical analyzer (Hitachi Chemical Co., Tokyo, Japan). Leptin and adiponectin were measured using radio immuno assay (RIA) (Millipore, St. Charles, MO). All nephelometric measurements were performed in duplicate in each of two optical systems. The average of these values was used for calculations.

Statistical Analysis 

Data are presented as mean, standard deviation, median, and range. The distribution of variables for normality was assessed using the Kolmogorov-Smirnov test.37 Variables that were non-normally distributed were log-transformed. Multivariate analyses used multiple linear regression analysis, with backward elimination (P < .1 for parameter retention in the model), and with biochemical markers as dependent variables. The independent variables were subcutaneous adipose tissue mass (SAT) or visceral adipose tissue mass (VAT) or total adipose tissue mass, measured by MRI adjusted for age, sex, presence of diabetes, weight, and race. We also analyzed the effect of VAT on cardiovascular risk factors, using VAT as a categorical variable. We divided the population into tertiles, and performed analysis of variance using Tukey's test for significance. We controlled for the effects of age, race, and sex. A two-sided P < .05 was considered significant. We used JMP 5.0.1 (SAS, Cary, NC) for statistical analyses.

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Results 

The median BMI was 27.3kg/m2 (range, 19.4-46.6kg/m2), the median age was 54.5 years (range, 33-80 years), and the median weight was 78.1kg (range, 43.1-120kg). The median total adipose tissue mass was 24.3kg (range, 6.2-57.9kg), the median subcutaneous adipose tissue mass was 20.3kg (range, 5.8-50.8kg), the median visceral adipose tissue mass was 3.25kg (range, 0.13-8.88kg), and the median skeletal muscle mass was 23.3kg (range, 12.2-36.9kg). Vintage ranged from 2 months to 15.3 years, with a median vintage of 2.8 years. Residual renal function, expressed as urea clearance, ranged from zero to 7.7mL/min. Only 9 patients had any urine output. Among those 9, the median residual clearance was 1.4mL/min. Medians and ranges of risk factor are shown in Table 1.

Table 1. Medians and Ranges of Risk Factors Among Dialysis Patients
CRP (g/L)5.0 (0.1-260)
IL-6 (pg/mL)5.5 (1-22)
α1 AG (mg/dL)106 (46-187)
Ceruloplasmin (mg/dL)42 (23-73)
HDL Cholesterol (mg/dL)43 (8-79)
Apo AI (mg/dL)131 (89-239)
Triglycerides (mg/dL)133 (36-436)
Apo CIII (mg/dL)15.0 (2.9-35.7)
Apo CII (mg/dL)3.2 (0.45-7.66)
LDL cholesterol (mg/dL)66 (13-142)
Remnant cholesterol (mg/dL)3.7 (2.1-9.1)
Total cholesterol (mg/dL)157 (83-236)
Apo B (mg/dL)60.9 (14.9-120)
Adiponectin (μg/mL)18.4 (5.9-59.4)
Leptin (ng/mL)9.85 (0.2-127.2)

AG, acid glycoprotein. Values are medians and ranges of risk factors in hemodialysis patients.

Inflammatory Markers 

According to simple linear regression analysis, CRP was positively associated with SAT (r2=0.11, P=.03), ceruloplasmin was positively associated with VAT (r2=0.16, P=.01) and SAT (r2=0.2, P < .005), and α1 acid glycoprotein was positively associated with SAT (r2=0.11, P=.03) (Table 2). After adjustment for demographic variables, the associations that remained significant were between both α1 acid glycoprotein and log CRP and SAT, and between ceruloplasmin and VAT (Table 3). Interleukin-6 was not significantly related to any measure of adiposity.

Table 2. Relationship Between Body Composition and Cardiovascular Risk Factors in Hemodialysis Patients
Relationship between acute-phase proteins and body composition according to univariate analysis
VATSAT
Log CRPNSP=.03
Log IL-6NSNS
α1 acid glycoproteinNSP=.03∗
CeruloplasminP=.01P=.005
Relationship between adipokines and body composition according to univariate analysis
VATSAT
Log leptin<0.0001<0.0001
Log adiponectin<0.0001∗0.003
Relationship between lipids and body composition according to univariate analysis
VATSAT
Total cholesterolNS0.012∗
Triglycerides0.0003∗0.03
LDLNSNS
HDLNSNS
Apo CII0.001∗0.006
Apo CIII0.002∗0.007
Apo BNSNS
Apo AINSNS

Univariate relationships between groups of risk factors, inflammatory markers, adipokines, lipoprotein levels, measures of adipose mass, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) in hemodialysis patients. All tissue compartments are in kilograms, and were measured using magnetic resonance imaging.

∗Remained significant when both SAT and VAT were entered into the relationship.

Table 3. Multivariate Analysis of Relationship Between Body Composition and Cardiovascular Risk Factors in Hemodialysis Patients
Dependent VariableIndependent VariableβStandard ErrortP ValueAdjusted r2Excluded Variables
Log CRPConstant−0.7090.169−4.187.0000.092Race, sex, age, VAT
SAT0.0160.0072.314.026
α1 acid glycoproteinConstant85.9879.6708.892.0000.087Race, sex, age, VAT
SAT0.9130.4052.254.029
CeruloplasminConstant20.9375.9553.516.0010.300Sex, age, SAT
VAT3.1810.8093.933.0001
Race (black)14.5435.0112.902.006
Apo CIIConstant1.0720.7061.519.137.275Age, SAT, sex
VAT0.4910.1204.077.0001
Race (black)1.1230.5761.949.059
Apo CIIIConstant9.1141.7145.317.0001.219Race, sex, SAT, age
VAT1.5710.4503.491.001
TriglyceridesConstant85.40021.6893.938.000.262Race, SAT, sex, age
VAT21.9655.7693.808.001
Log adiponectinConstant1.6180.07920.480.000.429Sex, SAT, age
VAT−0.0780.013−5.850.0001
Race (black)−0.1330.065−2.056.046
Log leptinConstant−0.1890.110−1.719.093.766Race, age, sex
SAT0.0470.0067.388<.0001
VAT0.0530.0301.735.090

Lipid Markers 

According to univariate analysis, TGs were correlated with VAT (r2=0.27, P=.0006) (Fig. 1 and Table 2). According to multiple regression analysis, TGs were significantly correlated only with VAT after controlling for age, sex, and race (Table 3). When VAT was used as a categorical variable, TGs were significantly greater in tertiles 3 and 2, compared with patients in the lowest tertile of VAT.

Apolipoprotein CII was correlated with VAT (r2=0.24, P=.001) and SAT (r2=0.18, P=.006) according to univariate analysis (Table 2). According to multiple regression analysis, apo CII was correlated with VAT after adjustment for age, sex, and race (Table 3). Apolipoprotein CII was significantly greater in patients in the upper two tertiles of VAT compared with tertile 1.

Similarly, apo CIII was correlated with VAT (r2=0.22, P=.0016) (Fig. 2) and total adipose tissue mass (r2=0.2, P=.003), according to univariate analysis (Table 2). According to multiple regression analysis, apo CIII was correlated positively with VAT after adjustment for age, sex, and race (Table 3). Apolipoprotein CIII was significantly greater in patients in the upper two tertiles of VAT compared with tertile 1.

  • View full-size image.
  • Figure 2 

    Relationship between serum apolipoprotein (apo) CIII and visceral adipose tissue (VAT) measured by magnetic resonance imaging in prevalent hemodialysis patients.

Neither HDL cholesterol, apo AI, nor LDL cholesterol was correlated with any measures of body composition. In contrast to other lipid markers, the r2 values were approximately zero, suggesting no effect of body composition on HDL or apo AI levels in these subjects.

Adipokines 

Adiponectin was significantly and inversely associated with SAT (r2=0.20, P=.0027) and VAT (r2=0.37, P < .0001). According to multiple regression analysis, adiponectin was only negatively associated with VAT (P < .00001), and was not affected by sex or any other anthropometric measurements (Table 3). The relationship between adiponectin and VAT (Fig. 3) was essentially identical between men and women. Adiponectin was significantly greater in patients in the first tertile of VAT compared with the second tertile (P < .01), and was significantly greater in the first tertile than in the second or third tertile.

  • View full-size image.
  • Figure 3 

    Relationship between serum adiponectin level and visceral adipose tissue (VAT) measured by magnetic resonance imaging in prevalent hemodialysis patients by sex. Men are represented by open circles, and women by open triangles.

Leptin (after log transformation) was positively associated with SAT (r2=0.766, P < .0001) and VAT (r2=0.47, P < .001) (Table 2) according to univariate analysis, but only with SAT according to multivariate analysis (r2 for the model=0.766, P < .0001) (Table 3).

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Discussion 

Mortality increases with increasing BMI, after a minimum mortality for BMIs between 23 and 26, in normal subjects.38, 39 Adiposity, especially visceral adiposity, is associated with cardiovascular disease,39, 40 hypertension,41 and other cardiovascular risk factors (increased TGs, LDL cholesterol, decreased HDL cholesterol, and inflammation)10 in patients with normal kidney function. Obesity, identified as waist-to-hip ratio, is also a risk factor for incident chronic kidney disease (CKD).42 Among patients who develop CKD, waist-to-hip ratio also was a risk factor for cardiovascular events.43 However, the mean glomerular filtration rate in this cohort was 51.1mL/min, so that the extrapolation of risk to that of the prevalent dialysis patient population may not be applicable.

The causal link between cardiovascular mortality and adiposity is proposed, at least in part, to be a consequence of alterations in blood-lipid levels and inflammation.15, 16, 44 In contrast to patients with normal renal function, BMI is associated with increased survival among dialysis patients, even at BMI values >39.1 Thus, obesity in dialysis patients must contribute some beneficial effect, or else specific risk factors linking mortality and adiposity must be mitigated.

We found that components of this relationship, especially the link between HDL cholesterol and apo AI, and to a lesser extent, the relationship between IL-6 and CRP and elements of adiposity, were obscured among dialysis patients. By contrast, the relationship between VAT and TG-rich lipoproteins was essentially preserved, as was the relationship between adiposity and adipokine levels.

The dyslipidemia of CKD, and specifically of the apo B-containing lipoproteins, is characterized by reduced clearance.45 Decreased clearance of these lipoproteins is attributable, in part, to intrinsic defects in the capacity of TG-rich lipoproteins to act as appropriate substrates for lipolytic enzymes,21 consistent with the presence of an intrinsic structural change in lipoproteins making them less susceptible to lipolysis by LPL. Apolipoprotein CIII is an inhibitor of the action of LPL on TG-rich lipoproteins,46, 47 and is increased in dialysis patients.20 Although levels of apo CIII were significantly greater than reported for normal subjects,48, 49 we found that apo CIII levels were associated with VAT within these subjects, similar to the relationship described in patients without renal failure.50 By contrast, LDL cholesterol was low for this population as a whole, and was not significantly associated with adiposity.

Inflammation is common among dialysis patients,51 and is well above the levels observed in nondialysis populations.3, 12 Inflammation is associated with the malnutrition, inflammation, and atherosclerosis syndrome,52 providing a basis for inflammation in nonobese subjects, and potentially obscuring an effect linked to adiposity. Among subjects with normal kidney function, the association between adiposity and either CRP and IL-6 is quite strong. However, the median values are significantly lower than we report here for dialysis patients.53 The upper tertile of CRP among patients without kidney disease begins at 3mg/L,54 a value below the median value among the dialysis patients we studied. Similarly, median IL-6 values were also well above the upper quartile (>2.28pg/mL) among the nondialysis population.14 Axelsson et al. reported an association between truncal fat mass and serum IL-6 levels; however, their r2 value was 0.044.55 By contrast, we found a strong association between the more long-lived acute-phase protein ceruloplasmin and VAT. Ceruloplasmin was associated with central obesity in patients not on dialysis.56 Serum IL-6 and CRP values are highly variable temporally in HD patients, far more so than are the levels of α1 acid glycoprotein or ceruloplasmin,57 possibly contributing to the decrease in association between these more variable proteins and the adipose pools. Thus, although inflammation and low HDL were found in this population, the risk was either not linked to adiposity at all, or only weakly linked to adiposity (CRP), primarily because of low HDL and increased inflammation, at least as reported by short-lived makers of inflammation, among lean dialysis patients. The risk factors were present regardless of adiposity, and present at a level associated with the highest level of cardiovascular risk in populations without kidney failure. Other factors that we did not control for may have obscured any effects of body composition.

Adiposity remained associated with TGs and with the cardiovascular risk factor apo CIII, and visceral adiposity was inversely associated with adiponectin. In contrast to patients without kidney failure, adiponectin was directly associated with mortality in dialysis patients by some investigators,23 and was indeterminate according to some,58 whereas a protective effect was noted by others.22 It is possible that adiponectin is not in the causal pathway linking body composition to outcome, and that it simply reflects adiposity, thus explaining the apparent salutary effect of high adiponectin in the population of patients without renal failure, with a possible deleterious effect observed by some investigators among populations of patients with kidney failure.23

We previously established, in a much larger group of patients (approximately 26,000), that the relationship between HDL cholesterol and BMI was lost as estimated glomerular filtration rate (eGFR) declined.59 The main limitation of the present study is that it is small. However, we directly measured both VAT, which is strongly associated with insulin resistance and dyslipidemia, and SAT, and found that many but not all risk factors associated with increased adiposity are increased in prevalent HD patients, regardless of total adiposity or visceral adipose mass. If these risk factors are on the causal pathway to cardiovascular mortality, the incremental risks imposed by these factors are not increased among obese dialysis patients. However, other risk factors specifically associated with TG-rich lipoproteins (TG and apo CIII levels) retain the same qualitative relationship to body composition in dialysis patients as they do in subjects with normal renal function. Why obese dialysis patients avoid an increased mortality risk despite the residual association between adiposity and these risk factors remains to be established.

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Acknowledgments 

Our research was supported by the Renal Research Institute, by a grant from Dialysis Clinic, Inc., and by the Western Human Nutrition Research Center and a grant from the National Institutes of Health PO1 DK-42618.

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PII: S1051-2276(09)00101-0

doi:10.1053/j.jrn.2009.04.002

Journal of Renal Nutrition
Volume 19, Issue 5 , Pages 357-364, September 2009

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