American Journal of Kidney Diseases
Volume 54, Issue 6 , Pages 1072-1080, December 2009

Soluble CD14 Levels, Interleukin 6, and Mortality Among Prevalent Hemodialysis Patients

  • Dominic S.C. Raj, MD

      Affiliations

    • Division of Renal Diseases and Hypertension, George Washington University, Washington, DC
    • ,
  • Juan J. Carrero, PhD

      Affiliations

    • Department of Renal Medicine, Karolinska Institutet, Stockholm, Sweden
    • ,
  • Vallabh O. Shah, PhD

      Affiliations

    • Department of Biochemistry, University of New Mexico Health Sciences Center, Albuquerque, NM
    • ,
  • Abdul R. Qureshi, MD

      Affiliations

    • Department of Baxter Novum, Karolinska Institutet, Stockholm, Sweden
    • ,
  • Peter Bárány, MD

      Affiliations

    • Department of Renal Medicine, Karolinska Institutet, Stockholm, Sweden
    • ,
  • Olof Heimbürger, MD

      Affiliations

    • Department of Renal Medicine, Karolinska Institutet, Stockholm, Sweden
    • ,
  • Bengt Lindholm, MD

      Affiliations

    • Department of Baxter Novum, Karolinska Institutet, Stockholm, Sweden
    • ,
  • Jennet Ferguson, BA

      Affiliations

    • Division of Renal Diseases and Hypertension, George Washington University, Washington, DC
    • ,
  • Pope L. Moseley, MD

      Affiliations

    • Department of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM
    • ,
  • Peter Stenvinkel, MD

      Affiliations

    • Department of Renal Medicine, Karolinska Institutet, Stockholm, Sweden
    • Corresponding Author InformationAddress correspondence to Peter Stenvinkel, MD, Department of Renal Medicine K56, Karolinska University Hospital at Huddinge, Karolinska Institutet, 141 86 Sweden

Received 8 January 2009; accepted 23 June 2009. published online 07 September 2009.

Article Outline

Background

CD14 is a pattern-recognition receptor that has a central immunomodulatory role in proinflammatory signaling in response to a variety of ligands, including endotoxin. CD14 protein is present in 2 forms: soluble (sCD14) and membrane bound. Here, we studied the implications of increased sCD14 levels in hemodialysis patients. We hypothesized that sCD14 level increase may link to cytokine activation and protein-energy wasting, predisposing to increased mortality risk.

Study Design

Prospective observational study of prevalent hemodialysis patients.

Setting & Participants

211 prevalent hemodialysis patients, median age of 65 years, with 29 months of vintage dialysis time followed up for mortality for a median of 31 months.

Predictors

Tertiles of baseline circulating sCD14 levels corresponding to less than 2.84, 2.85 to 3.62, and greater than 3.63 μg/mL.

Outcome

The major outcome of interest was all-cause mortality.

Measurements

sCD14 and endotoxin, together with other markers of inflammation and protein-energy wasting.

Results

Median sCD14 level was 3.2 μg/mL (25th to 75th percentile, 2.7 to 3.9). sCD14 level correlated positively with C-reactive protein, interleukin 6, endotoxin, and pentraxin 3 levels and negatively with serum albumin level, muscle mass, and handgrip strength. Patients with increased sCD14 levels had lower body mass index and increased prevalence of muscle atrophy. Patients within the highest sCD14 tertile had a crude morality hazard ratio of 1.94 (95% confidence interval, 1.13 to 3.32) that persisted after adjustment for multiple confounders (hazard ratio, 3.11; 95% confidence interval, 1.49 to 6.46). In patients with persistent inflammation, the presence of a concurrent sCD14 level increase gradually increased mortality risk, but this effect was less than multiplicative and failed to show a statistical interaction.

Limitations

Those inherent to an observational study.

Conclusions

sCD14 level is associated with inflammation and protein-energy wasting in hemodialysis patients. It is a strong and independent predictor of mortality that warrants further assessment in the clinical setting regarding its usefulness as a complementary prognosticator to other general inflammatory markers.

Index Words: Endotoxin, interleukin 6 (IL-6), protein-energy wasting, C-reactive protein (CRP), hemodialysis, pentraxin 3

 

Editorial, p. 990

Although the mechanisms explaining the increased mortality risk of patients with end-stage renal disease (ESRD) are not yet fully elucidated, both protein-energy wasting (PEW)1 and inflammation2 strongly augment the hazards of death. Inflammation has been proposed as the central integrating factor linking PEW and cardiovascular disease (CVD) in patients with ESRD, and although the cause of unprovoked inflammation in the uremic milieu essentially is unknown, both dialysis-related and dialysis-unrelated factors are likely to contribute.3, 4 One potentially important, yet scarcely explored, source of inflammation in patients with ESRD is subclinical endotoxemia because transmembrane passage of lipopolysaccharide (LPS) fragments may constitute an important cause of immune activation in dialysis patients.5, 6 CD14 is a pattern-recognition receptor that has a central immunomodulatory role in proinflammatory signaling in response to a variety of ligands, including endotoxin and other bacterial products from both Gram-negative and Gram-positive bacteria.7 An LPS concentration as low as 0.01 ng/mL induces upregulation of CD14 expression,8 stimulating activation of cytokines, myokines, and adipokines.9, 10 CD14 protein is present in 2 forms: soluble (sCD14) and membrane bound. Although membrane-bound CD14 binds LPS and induces the release of proinflammatory cytokines and reactive oxygen species,11 sCD14 increases in response to LPS challenge and is derived from both secretion of CD14 and enzymatic cleavage.7

In individuals without kidney disease, increased sCD14 levels have been related to aortic stiffness and metabolic disorders, including hypertriglyceridemia, insulin resistance, and activation of the inflammatory cascade.12, 13 In hemodialysis (HD) patients, increased CD14 expression and increased sCD14 serum levels have been reported.8 Heine et al14 recently showed that the number of CD14++ monocytes was predictive of cardiovascular events and death in a dialysis population. However, the phenotype associated with increased levels of sCD14 and its links to endotoxin in dialysis patients have not been well explored. In this study, we hypothesized that increased sCD14 levels predispose to increased mortality risk. We therefore examined the association between plasma sCD14 concentrations with other inflammatory and PEW markers, as well as its implications on outcome in a carefully phenotyped cohort of prevalent HD patients.

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Methods 

Patients and Experimental Design 

This study includes prevalent patients undergoing HD at 5 dialysis units in Stockholm and 1 in Uppsala, Sweden. In all participating dialysis units and at the time of blood extraction, water conductivity was less than 1 μS/cm, the number of viable microorganisms was less than 100/mL, and endotoxin concentration was less than 0.25 IU/mL. According to hospital protocols, dialysis filters were not reused. This is a post hoc analysis of a cross-sectional study that originally aimed to investigate the variability of inflammatory markers in HD patients.15 Patient recruitment and baseline sampling took place between October 2003 and September 2004. From 254 patients invited to participate, several exclusions were made because of unwillingness to participate (n = 6) and human immunodeficiency virus (HIV) infection (n = 1). When the study was finalized, additional exclusions were made because of insufficient clinical information (n = 18) and sudden death (n = 1). Thus, 228 patients were included in the study and followed up for assessment of overall and cardiovascular mortality. From this material, sCD14 and endotoxin levels could be determined in only 211 because not enough plasma was available for 16 patients and sCD14 values were outside the calibration range for 1 additional patient. A comparison between included and excluded patients did not show a major population difference with regard to age, sex distribution, dialysis vintage, or body weight (not shown). Survival was determined from the day of examination until March 10, 2007, with a mean follow-up of 31 months (25th to 75th percentile, 21 to 37 months). There was no loss to follow-up of any patient. The study protocols were approved by the Ethics Committee of Karolinska Institutet and Uppsala University. Signed informed consent was obtained from all patients.

Laboratory Analyses 

Blood samples were collected before the HD session after the longest interdialytic period. Plasma and serum were separated and kept frozen at −70°C if not analyzed immediately. Serum interleukin 6 (IL-6) levels were quantified by using immunometric assays on an Immulite Analyzer (Siemens Medical Solutions Diagnostics, Los Angeles, CA) according to the manufacturer's instructions. Plasma pentraxin 3 (PTX3) was measured by using a commercially available enzyme-linked immunosorbent assay (ELISA) kit (Perseus Proteomics, Inc, Tokyo, Japan). High-sensitivity C-reactive protein (hs-CRP), fibrinogen, serum albumin, serum creatinine, total cholesterol, triglycerides, and hemoglobin concentrations and percentage of hypochromic red blood cells were analyzed by using certified methods at the Department of Laboratory Medicine in Karolinska University Hospital or Uppsala Academic Hospital. We used the quantitative chromogenic limulus amebocyte lysate test for endotoxins in plasma (both free and protein-bound forms) by using a commercially available kit (QCL-1000; Cambrex Bioscience Inc, Walkersville, MD) following the manufacturer's instructions. The lower limit of detection is 0.01 EU/mL, and the coefficient of variation is 3% to 9%. sCD14 was measured by using a commercially available ELISA kit (sCD14 Quantikine ELISA Kit; R&D Systems, Minneapolis, MN). Interassay and intra-assay coefficients of variations are less than 7.5% and less than 6.5%, respectively. All samples were measured in triplicate, and the mean value was used.

Nutritional Status and Anthropometric Evaluation 

Body mass index (BMI) and anthropometric and dynamometric measurements were determined on a dialysis day. Height was obtained from the patient's chart. Fat mass and lean body mass were assessed according to Durnin et al16 by using the 4 skinfold thicknesses (biceps, triceps, subscapular, and suprailiac), measured using a conventional skinfold caliper (Cambridge Scientific Instruments, Cambridge, MD). Midarm circumference was measured using a plastic tape. Midarm muscle circumference was calculated by using the following formula: Midarm circumference − π × triceps skinfold thickness.16 Handgrip strength was measured in both the dominant and nondominant hands by using a Harpenden Handgrip Dynamometer (Yamar, Jackson, MI). Each measurement was repeated 3 times for each arm, and the greatest value for each arm was noted. For our analysis, we used the arm contralateral to the fistula/graft arm. Subjective Global Assessment (SGA) was used to evaluate overall PEW.17 PEW was defined for the purpose of this study as SGA greater than 1. This assessment was performed either at the time of or within 1 week of blood sample collection. Estimation of the presence of muscle atrophy is part of the SGA questionnaire, which recently has been validated as a useful muscle assessment in dialysis patients.18

Statistical Analyses 

All variables are expressed as mean ± SD or median and 25th to 75th percentile, unless otherwise indicated. Statistical significance was set at P < 0.05. Differences among more than 2 groups were analyzed by means of analysis of variance using 1-way analysis of variance or Kruskal-Wallis test, as appropriate. Spearman rank correlation (ρ) was used to determine correlations of sCD14 levels with other variables. Multinomial logistic regression analyses were used to study variables associated with sCD14 levels in this patient population. Selection of the confounders in this model was performed on the basis of sCD14 pathophysiological characteristics, and all covariates satisfied the proportional odds assumption. Restricted cubic splines were used to evaluate nonlinear relationships between sCD14 levels and outcome.19 We chose 4 knots at quantiles, which has been suggested to offer adequate fit of the model and is a good compromise between flexibility and loss of precision caused by overfitting a small sample.20 Thereafter, univariate and multivariate Cox regression analyses based on tertile distribution were presented as hazard ratio and 95% confidence interval. To avoid the possibility that patients within dialysis centers may have correlated time to event, we adjusted for center as a fixed effect in the Cox models. All covariates satisfied the proportional hazards assumption. Because it has been suggested that persistent inflammation may influence effects of increased levels of CD14++CD16+ monocytes on adverse outcomes,14 the statistical interaction between sCD14 and IL-6 levels was tested by the inclusion of the product term of these 2 variables. Statistical computations were carried out using SAS, version 9.1.3 (SAS Institute, Cary, NC). Because P values are not adjusted for multiple testing, they have to be considered as descriptive.

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Results 

Patient Characteristics 

Patients underwent HD 3 times weekly (4 to 5 h/session) using bicarbonate dialysate. Most patients used polyamide membranes (59%), followed by polysulfone (35%). Regarding vascular access, 58% had an arteriovenous fistula, whereas 22% and 20% had grafts and central dialysis catheters, respectively. Additional baseline and prescription data are listed in Table 1. Most patients were using antihypertensive medications (β-blockers [n = 104; 49%], calcium channel blockers [n = 51; 21%], and angiotensin-converting enzyme inhibitors/angiotensin receptor blockers [n = 67; 31%]), as well as other drugs commonly used in patients with ESRD (such as phosphate and potassium binders) and vitamin B, C, and D supplementation. Sixty-four patients (30%) were using lipid-lowering medication (statins). One hundred ninety-six patients (93%) were receiving erythropoiesis-stimulating agents at the time of evaluation. Weekly doses of darbepoetin in micrograms were converted to international units of erythropoietin by multiplying with the conversion factor of 200. Median erythropoiesis-stimulating agent dose was equivalent to 10,000 U/wk (25th to 75th percentile, 6,000 to 14,750), which was normalized for body weight and presented as units per kilogram per week.

Table 1. Patient Characteristics and Biochemical Profile of All Patients According to Tertiles of Soluble CD14 Distribution
All Patients (N = 211)Low Tertile; <2.84 μg/mL (n = 70)Middle Tertile; 2.85-3.62 μg/mL (n = 70)High Tertile; >3.63 μg/mL (n = 71)P
Age (y)65(50-74)63(48-76)67(49-75)64(51-73)0.3
Vintage (mo)29(15-57)26(14-51)31(12-57)31(18-70)0.7
Men (%)566460450.06
Protein-energy wasting (%)474446510.7
Diabetes mellitus (%)232326210.8
Cardiovascular disease (%)636164620.9
High-sensitivity C-reactive protein (mg/L)6.5(2.5-21.0)4.9(1.5-11.3)6.0(2.5-21.0)10.0(4.2-26.0)0.001
Interleukin 6 (pg/mL)8.5(4.9-15.0)6.2(4.1-10.8)8.6(5.6-15.0)10.1(6.3-21.6)0.001
Pentraxin 3 (ng/mL)10.3(7.0-17.0)2.4(2.1-2.7)3.2(3.0-3.4)4.2(3.9-4.8)<0.001
Fibrinogen (mg/dL)420(340-525)380(330-470)445(368-525)425(360-560)0.04
Albumin (g/dL)3.5±0.53.5±0.43.4±0.43.3±0.50.01
Endotoxin (EU/mL)0.65(0.43-1.16)0.42(0.34-0.87)0.71(0.47-0.95)0.80(0.51-2.65)<0.001
Body mass index (kg/m2)24.3±5.124.2±5.125.5±5.323.3±8.00.01
Lean body mass (kg)48.1±10.449.3±10.449.8±11.145.2±9.30.02
Fat body mass (kg)22.6±8.422.4±8.223.9±7.921.3±8.90.08
Midarm muscle circumference (cm)24.2±3.624.4±3.624.8±3.223.2±3.70.008
Handgrip strength (%)62.1±22.661.1±24.052.2±23.048.4±22.00.02
Erythropoiesis-stimulating agents (U/kg/wk)134(82-210)120(74-181)116(74-187)180(115-255)0.001
Hemoglobin (g/dL)11.9±1.311.9±1.211.9±1.31.17±1.40.3
Hypochromic red blood cells (%)1.3(0.7-3.4)1.0(0.4-1.6)1.1(0.5-3.7)2.5(0.9-3.9)0.003

Note: Values expressed as median (25th to 75th percentile) or mean ± SD unless noted otherwise. Conversion factors for units: serum albumin in g/dL to g/L, ×10.

Plasma sCD14 and Endotoxin Levels 

Median sCD14 and endotoxin levels were 3.2 μg/mL (25th to 75th percentile, 2.7 to 3.9) and 0.65 EU/mL (25th to 75th percentile, 0.43 to 1.16), respectively. sCD14 levels were significantly greater in women compared with men (3.5 [25th to 75th percentile, 2.8 to 4.0] versus 3.1 μg/mL [25th to 75th percentile, 2.7 to 3.7]; P = 0.02). Plasma sCD14 levels were not increased in patients with diabetes or those with a clinical history of previous cardiovascular events (data not shown). Current smokers had greater (P = 0.03) sCD14 values (3.4 μg/mL; 25th to 75th percentile, 3.0 to 4.1; n = 41) than former smokers (3.0 μg/mL; 25th to 75th percentile, 2.6 to 3.6; n = 94) and nonsmokers (3.2 μg/mL; 25th to 75th percentile, 2.5 to 4.0; n = 68). Patients on statin (3.0 versus 3.3 μg/mL; n = 64 of 147; P = 0.03), angiotensin-converting enzyme–inhibitor or angiotensin receptor blocker (2.9 versus 3.4 μg/mL; n = 67 of 143; P = 0.003), β-blocker (3.0 versus 3.4 μg/mL; n = 104 of 107; P = 0.02), or acetylsalicylic acid derivate therapy (3.0 versus 3.3 μg/mL; n = 63 of 148; P = 0.05) had significantly lower median sCD14 levels. No difference was found in endotoxin levels with regard to sex, smoking status, different comorbidities, and medication prescriptions.

Variables Related to sCD14 and Endotoxin Levels in HD Patients 

As expected, in univariate analysis, sCD14 levels were related positively to levels of inflammatory markers, such as hs-CRP (ρ = 0.30; P < 0.001), IL-6 (ρ = 0.26; P < 0.001), PTX3 (ρ = 0.24; P < 0.001), and fibrinogen, as well as blood lipid levels (cholesterol and triglycerides), erythropoiesis-stimulating agent dose, and percentage of hypochromic red blood cells. There also was a positive correlation with endotoxin values (ρ = 0.21; P < 0.001), but not white blood cell or lymphocyte count (not shown). At the same time, sCD14 levels showed negative associations with serum albumin levels (ρ = −0.20; P = 0.008) and surrogates of muscle mass (lean body mass [ρ = −0.19; P = 0.009], midarm muscle circumference [ρ = −0.20; P = 0.008], and handgrip strength [ρ = −0.19; P = 0.008]), but not fat body mass or creatinine level. Because of the observed association between muscle strength and sCD14 levels, patients were divided according to the subjective grading of muscle atrophy (included in the SGA). Patients with no signs of muscle atrophy had a lower median sCD14 level (3.0 μg/mL; 25th to 75th percentile, 2.5 to 3.7; n = 131) than those with mild (3.3 μg/mL; 25th to 75th percentile, 2.8 to 3.8; n = 49) or severe (3.9 μg/mL; 25th to 75th percentile, 2.1 to 4.7; n = 25) signs of muscle atrophy (P = 0.002). Finally, we performed multinomial logistic regression analysis searching for predictors of sCD14 level. Sex, IL-6 level, and endotoxin level were related to greater odds of having increased plasma sCD14 concentrations (Table 2). Whereas endotoxin values were related to age (ρ = −0.14; P = 0.04), erythropoiesis-stimulating agent dose (ρ = −0.13; P = 0.04), hemoglobin level (ρ = 0.18; P = 0.009), and triglyceride level (ρ = 0.24; P < 0.001), no significant association was found with inflammatory markers.

Table 2. Odds Ratios and 95% Confidence Intervals for Tertiles of sCD14 Distribution in a Multinomial Logistic Regression Including 211 Prevalent Hemodialysis Patients
Odds Ratio (95% confidence interval)P
Interleukin 6, middle v low tertile1.97(0.99-3.93)0.05
Interleukin 6, high v low tertile4.74(2.30-9.77)<0.001
Sex, women v men0.35(0.19-0.62)<0.001
Age, 45-65 v ≤45 y0.79(0.33-1.89)0.6
Age, ≥65 v ≤45 y0.65(0.27-1.53)0.3
Endotoxin, middle v low tertile2.37(1.22-4.63)0.01
Endotoxin, high v low tertile5.35(2.67-10.74)<0.001

Note: Pseudo r2 for this model equals 0.20. The independent variable was sCD14 levels divided into ordered tertiles of distribution, choosing the lowest sCD14 tertile as the reference. Interleukin 6 tertiles were defined as follows: low tertile, 6.03 or less pg/mL; middle tertile, 6.04 to 11.35 pg/mL; high tertile, 11.36 or greater pg/mL. Endotoxin tertiles were defined as follows: low tertile, 0.48 or less EU/mL; middle tertile, 0.48 to 0.88 EU/mL; high tertile, 0.89 or greater EU/mL.

Abbreviation: sCD14, soluble CD14.

Tertiles of sCD14 Distribution 

Study participants were divided into tertiles of sCD14 distribution (Table 1). Across increasing sCD14 tertiles, there was a trend toward an increased proportion of women. Also, patients within the higher tertile of sCD14 distribution more often had inflammation and greater endotoxin values. They also had a lower BMI (attributed to decreased lean body mass rather than a decrease in fat body mass) and lower handgrip strength and midarm muscle circumference values. Finally, across increasing sCD14 tertiles, incrementally greater erythropoietin doses and percentages of hypochromic red blood cells were observed.

Impact of sCD14 on Survival and Relative Risks 

During follow-up, 78 patients died. Age- and sex-adjusted spline curves showed that only greater sCD14 concentrations have an impact on mortality (Fig 1). Thus, we used the strategy of tertile distribution to distinguish the group of patients within the upper side of the hyperbole. Compared with the lower sCD14 tertile, patients in the top tertile of distribution remained at greater risk of death during follow-up, even after various adjustments (Table 3).

  • View full-size image.
  • Figure 1. 

    Spline curve shows log-transformed hazard ratios and 95% confidence intervals (dashed line) for all-cause mortality associated with soluble CD14 (sCD14) values in 211 prevalent hemodialysis patients. The model is plotted as restricted cubic splines with 4 knots and adjusted for age and sex. P for linearity = 0.4.

Table 3. Cox Regression Analysis for All-Cause Mortality
Middle sCD14 TertilePHigh sCD14 TertileP
Unadjusted0.98(0.54-1.81)0.91.94(1.13-3.32)0.01
Adjusted
Model 10.98(0.51-1.83)0.93.05(1.56-5.89)<0.001
Model 20.91(0.46-1.84)0.83.11(1.49-6.46)0.002

Note: Indicated are hazard ratios, their 95% confidence intervals, and levels of significance. The low sCD14 tertile was considered the reference. Model 1 includes tertiles of sCD14 distribution after adjustment for age, sex, smoking habits, prevalence of cardiovascular disease and diabetes, and dialysis center; model 2 further adjusted for medication impacting on sCD14 level (statins, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, β-blockers, and acetylsalicylic acid), vintage, interleukin 6 level, and protein-energy wasting (Subjective Global Assessment > 1).

Abbreviation: sCD14, soluble CD14.

Cross-Classification of IL-6 and sCD14 

The prognostic value of sCD14 level was independent of inflammation (Table 2). However, because it has been suggested that the effect of increased CD14++CD16+ monocyte levels on death counts is magnified in the presence of a persistently inflamed environment,14 we tried to confirm this postulate by studying the prognostic use of sCD14 in the presence or absence of concomitant increased IL-6 levels. For this purpose, different groups with high and low concentrations were established according to median sCD14 and IL-6 values and cross-classified. The proportion of patients who died during follow-up increased across incremental groups of sCD14 levels for any group of IL-6 levels (Table 4). Whereas groups with inflammation were associated with worse survival, a moderate gain in prognostication and greater death count were observed when both increased IL-6 and increased sCD14 levels were present. However, statistical interaction analysis failed to show a departure from multiplicity of effects (crude hazard ratio for the product term sCD14 × IL-6, 0.89; 95% confidence interval, 0.62 to 1.29; P = 0.6).

Table 4. Crude All-Cause Mortality Risk According to Median sCD14 and IL-6 Levels Cross-Combined
No. of Deaths (%)Hazard Ratio (95% confidence interval)P
Low IL-6, low sCD1413(17)1.00
Low IL-6, high sCD1411(14)1.25(0.56-2.79)0.6
High IL-6, low sCD1418(23)2.36(1.15-4.82)0.01
High IL-6, high sCD1436(46)3.71(1.96-7.01)<0.001

Note: Groups are created according to median IL-6 (8.5 pg/mL) and sCD14 (3.2 μg/mL) levels in the study population.

Abbreviations: IL-6, interleukin 6; sCD14, soluble CD14.

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Discussion 

We have shown that sCD14 levels are associated positively with surrogate markers of inflammation, such as hs-CRP, IL-6, and PTX3 levels, in a carefully phenotyped cohort of prevalent HD patients followed up for a median of 41 months. Furthermore, patients with greater sCD14 levels had lower BMI, decreased muscle strength, and overt evidence of muscle atrophy. Finally, survival analysis showed that patients within the highest tertile of sCD14 distribution had the worst survival irrespective of multiple confounders. Altogether, the present study evidences a detrimental linkage between sCD14 levels and markers of inflammation, PEW, and mortality in HD patients.

Lipid A (endotoxin), the hydrophobic anchor of LPS, is a glucosamine-based phospholipid that makes up the outer monolayer of the outer membranes of most Gram-negative bacteria.5 The endotoxin concentration observed in our patients is similar to that reported previously in HD21 and peritoneal dialysis patients.22 Combined use of bicarbonate-buffered dialysate and highly permeable dialyzer HD membranes could potentially increase the risk of reverse transfer of dialysate contaminants, including endotoxin fragments, into the blood compartment.8, 23 Endotoxin level has been associated positively with atherosclerosis in the general population24 and patients with ESRD.22 However, we did not observe a significant association between plasma endotoxin levels and markers of inflammation, body composition, or mortality. This may be caused in part by the characteristics of our study design and the dialysis procedure in our centers, but also because endotoxin mediates the clinical response through interaction with such various specific receptors as sCD14, lipoprotein-binding protein, and bactericidal/permeability-increasing protein.25, 26 Also, our analysis measured both free and protein-bound endotoxins. In parallel, we also could observe in both univariate and multivariate analysis that endotoxin was significantly, but weakly, associated with sCD14. This may occur because of the complex endotoxin-sCD14 interaction. Although sCD14 receptor mediates the inflammatory response of endotoxin, the same receptor also promotes its clearance and neutralization.27, 28 Furthermore, low concentrations of endotoxin act through membrane-bound CD14, and high concentrations of endotoxin, through sCD14.7 Thus, it also is possible that measuring solely sCD14 may provide an incomplete view of the effects of this molecule. In our results, different medication prescriptions, such as statins, were associated with lower sCD14 levels, in accordance with previous reports showing that statin use leads to reduced sCD14 expression, linking the pleitropic anti-inflammatory effects of statins to its capacity to attenuate LPS responsiveness.29 Finally, immune responsiveness has been reported to be greater in women than men,30 and we found that sCD14 levels were significantly greater in the women in our study. In contrast, Temple et al31 showed that although the percentage of cells expressing intracellular Toll-like receptor-4 protein in response to LPS challenge was greater in male versus female healthy individuals, no sex difference in CD14 expression was observed.

Not surprisingly, we observed an association between levels of sCD14 and markers of inflammation, such as hs-CRP, IL-6, and PTX3. The latter association with PTX3 deserves attention because pentraxins are a family of multimeric pattern-recognition receptors that are divided into 2 groups based on the primary structure of the subunit as short pentraxins and long pentraxins. CRP and serum amyloid P-component are classic short pentraxins, whereas the prototype of the long pentraxin family is PTX3.32 PTX3 is expressed in a variety of cell types in response to inflammatory cytokines and Toll-like receptor engagement. Increased PTX3 levels in patients with ESRD are related to CVD, PEW, and increased mortality,33 being closely related to the development of albuminuria and endothelial dysfunction.34 Nonetheless, because sCD14 level was not related to white blood cell or lymphocyte count in our study, we cannot directly extrapolate our findings with those of CD14++-activated monocytes.14

Another interesting finding in our study is the association of sCD14 levels with markers of muscle mass and PEW, indicating cross-talk between inflammatory molecules and nutritional status in dialysis patients. sCD14 level has been related previously to insulin resistance,13 muscle wasting,35 atherosclerosis,12 and acute myocardial infarction in the general population.36 PEW and inflammation are common phenomena that usually occur concurrently in maintenance dialysis patients.37 PEW is associated with abnormal cardiac geometry,38 atherosclerosis,2 and increased mortality in patients with ESRD.38, 39 Many structural and functional alterations in skeletal muscles contribute to limited work capacity in patients with ESRD.40 Patients with greater sCD14 levels had evidence of lower BMI, muscle atrophy, and lower handgrip strength in our study. Although Fernández-Real et al13 did not observe an association between sCD14 level and BMI in 123 healthy well-nourished individuals without inflammation and with normal renal function, these results are not fully comparable to ours because cytokine retention in dialysis patients may substantially exaggerate the links between persistent inflammation and PEW.1 We previously reported that cytokine expression is increased in skeletal muscle after HD and is related to muscle protein breakdown and acute-phase protein synthesis.41, 42 Because exposure to LPS induces cytokine expression in skeletal muscles in a dose-dependent manner,9 this may establish altogether a link between endotoxin-sCD14 activation and PEW through increased muscle atrophy.

The present study shows that sCD14 level is independently associated with patient mortality. Consequently, we could observe that, in agreement with a previous study using CD14++CD16+ monocytes,14 only the highest sCD14 tertile was associated persistently with increased mortality irrespective of traditional and nontraditional risk confounders. Thus, our results are in accordance with those of Ulrich et al,43 who showed that activated CD14++CD16+ monocytes presented increased angiotensin-converting enzyme expression, evidencing the prominent role of these proinflammatory cells in atherogenesis. Because Heine et al14 observed a higher death count across different CRP and CD14++CD16+ monocyte groups, they hypothesized that the effect of CD14 activation on mortality was magnified in the presence of a concomitant increase in CRP levels. In agreement with this observation, we found a moderate gain in prognostication when both IL-6 and sCD14 levels were included in the model. However, because this effect failed to show a departure from multiplicity of effects, a statistical interaction could not be shown. Because we cannot exclude insufficient power to show these interaction effects, this should be reassessed in larger materials.

When interpreting our findings, the following limitations should be taken into consideration. First, our cross-sectional design precludes from causality. Second, the classification of CVD included only patients with clinically significant vascular disease, which may underestimate the true prevalence of CVD. Third, the prevalent nature of our cohort may represent a selection of patients who have survived CVD or survived despite the presence of factors potentially contributing to increased cardiovascular risk. Fourth, we lack information regarding volume status, which may influence our findings. Finally, we based our determinations on single measurements of inflammatory markers that are subjected to certain variability over time.44

To summarize, sCD14 level is associated positively with various markers of inflammation, but negatively with BMI, lean body mass, and muscle strength. At the same time, sCD14 level emerged as an independent predictor of mortality. Additional studies need to examine the relationship between circulating endotoxin and sCD14 levels in the inflamed uremic milieu and their effect on vascular health and outcome measures. This may lead to better prognostication and risk stratification in dialysis patients.

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Acknowledgements 

We thank the patients and personnel involved in the creation of this cohort and our research staff at KBC (AnneLie Stråhle, Ann Dreiman-Lif, Annika Nilsson, and Anki Emmoth) and KFC (Björn Anderstam, Monica Ericsson, and Anki Bragfors-Helin).

Support: The MIMICK cohort was supported by an unrestricted project grant from Amgen Inc. We also benefited from Karolinska Institutet Center for Gender-based Research, Karolinska Institutet research funds, MEC (EX2006-1670), the Swedish Heart and Lung Foundation, the Swedish Medical Research Council, Scandinavian Clinical Nutrition AB, and the Westman and Loo and Hans Ostermans Foundations. Endotoxin and sCD14 analyses were supported by National Institutes of Health (R01DK073665) and Norman Coplon research grants.

Financial Disclosure: Dr Lindholm is employed by Baxter Healthcare Inc.

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References 

  1. Fouque D, Kalantar-Zadeh K, Kopple J, et al. A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease. Kidney Int. 2007;73:391–398
  2. Stenvinkel P, Heimburger O, Paultre F, et al. Strong association between malnutrition, inflammation, and atherosclerosis in chronic renal failure. Kidney Int. 1999;55:1899–1911
  3. Carrero JJ, Yilmaz MI, Lindholm B, Stenvinkel P. Cytokine dysregulation in chronic kidney disease: How can we treat it?. Blood Purif. 2008;26:291–299
  4. Stenvinkel P, Carrero JJ, Axelsson J, Lindholm B, Heimburger O, Massy Z. Emerging biomarkers for evaluating cardiovascular risk in the chronic kidney disease patient: How do new pieces fit into the uremic puzzle?. Clin J Am Soc Nephrol. 2008;3:505–521
  5. Raetz CR, Whitfield C. Lipopolysaccharide endotoxins. Annu Rev Biochem. 2002;71:635–700
  6. Sundaram S, Barrett TW, Meyer KB, et al. Transmembrane passage of cytokine-inducing bacterial products across new and reprocessed polysulfone dialyzers. J Am Soc Nephrol. 1996;7:2183–2191
  7. Pugin J, Heumann ID, Tomasz A, et al. CD14 is a pattern recognition receptor. Immunity. 1994;1:509–516
  8. Nockher WA, Scherberich JE. Monocyte cell-surface CD14 expression and soluble CD14 antigen in hemodialysis: Evidence for chronic exposure to LPS. Kidney Int. 1995;48:1469–1476
  9. Lang CH, Silvis C, Deshpande N, Nystrom G, Frost RA. Endotoxin stimulates in vivo expression of inflammatory cytokines tumor necrosis factor alpha, interleukin-1beta, -6, and high-mobility-group protein-1 in skeletal muscle. Shock. 2003;19:538–546
  10. Grunfeld C, Zhao C, Fuller J, et al. Endotoxin and cytokines induce expression of leptin, the ob gene product, in hamsters. J Clin Invest. 1996;97:2152–2157
  11. Wright SD, Ramos RA, Tobias PS, Ulevitch RJ, Mathison JC. CD14, a receptor for complexes of lipopolysaccharide (LPS) and LPS binding protein. Science. 1990;249:1431–1433
  12. Amar J, Ruidavets JB, Bal Dit SC, et al. Soluble CD14 and aortic stiffness in a population-based study. J Hypertens. 2003;21:1869–1877
  13. Fernández-Real JM, Broch M, Richart C, Vendrell J, Lopez-Bermejo A, Ricart W. CD14 monocyte receptor, involved in the inflammatory cascade, and insulin sensitivity. J Clin Endocrinol Metab. 2003;88:1780–1784
  14. Heine GH, Ulrich C, Seibert E, et al. CD14(++)CD16+ monocytes but not total monocyte numbers predict cardiovascular events in dialysis patients. Kidney Int. 2008;73:622–629
  15. Carrero JJ, Qureshi AR, Axelsson J, et al. Comparison of nutritional and inflammatory markers in dialysis patients with reduced appetite. Am J Clin Nutr. 2007;85:695–701
  16. Durnin JV, Womersley J, Womersley J, Boddy K, King PC, Durnin JV. Body fat assessed from total body density and its estimation from skinfold thickness: Measurements on 481 men and women aged from 16 to 72 years. Br J Nutr. 1974;32:77–97
  17. Detsky AS, McLaughlin JR, Baker JP, et al. What is subjective global assessment of nutritional status?. JPEN J Parenter Enteral Nutr. 1987;11:8–13
  18. Carrero JJ, Chmielewski M, Axelsson J, et al. Muscle atrophy, inflammation and clinical outcome in incident and prevalent dialysis patients. Clin Nutr. 2008;27:557–564
  19. Heinzl H, Kaider A. Gaining more flexibility in Cox proportional hazards regression models with cubic spline functions. Comput Methods Programs Biomed. 1997;54:201–208
  20. Harrell F. Regression Modelling Strategies With Applications to Linear Models (Logistic Regression, and Survival Analysis). New York, NY: Spinger-Verlag; 2001;
  21. Nisbeth U, Hallgren R, Eriksson O, Danielson BG. Endotoxemia in chronic renal failure. Nephron. 1987;45:93–97
  22. Szeto CC, Kwan BC, Chow KM, et al. Endotoxemia is related to systemic inflammation and atherosclerosis in peritoneal dialysis patients. Clin J Am Soc Nephrol. 2008;3:431–436
  23. Pereira BJ, Snodgrass BR, Hogan PJ, King AJ. Diffusive and convective transfer of cytokine-inducing bacterial products across hemodialysis membranes. Kidney Int. 1995;47:603–610
  24. Wiedermann CJ, Kiechl S, Dunzendorfer S, et al. Association of endotoxemia with carotid atherosclerosis and cardiovascular disease: Prospective results from the Bruneck Study. J Am Coll Cardiol. 1999;34:1975–1981
  25. Fenton MJ, Golenbock DT. LPS-binding proteins and receptors. J Leukoc Biol. 1998;64:25–32
  26. Marra MN, Wilde CG, Collins MS, Snable JL, Thornton MB, Scott RW. The role of bactericidal/permeability-increasing protein as a natural inhibitor of bacterial endotoxin. J Immunol. 1992;148:532–537
  27. Wurfel MM, Hailman E, Wright SD. Soluble CD14 acts as a shuttle in the neutralization of lipopolysaccharide (LPS) by LPS-binding protein and reconstituted high density lipoprotein. J Exp Med. 1995;181:1743–1754
  28. Kitchens RL, Wolfbauer G, Albers JJ, Munford RS. Plasma lipoproteins promote the release of bacterial lipopolysaccharide from the monocyte cell surface. J Biol Chem. 1999;274:34116–34122
  29. Methe H, Kim JO, Kofler S, Nabauer M, Weis M. Statins decrease Toll-like receptor 4 expression and downstream signaling in human CD14+ monocytes. Arterioscler Thromb Vasc Biol. 2005;25:1439–1445
  30. Schuurs AH, Verheul HA. Effects of gender and sex steroids on the immune response. J Steroid Biochem. 1990;35:157–172
  31. Temple SE, Pham K, Glendenning P, Phillips M, Waterer GW. Endotoxin induced TNF and IL-10 mRNA production is higher in male than female donors: Correlation with elevated expression of TLR4. Cell Immunol. 2008;251:69–71
  32. Mantovani A, Garlanda C, Doni A, Bottazzi B. Pentraxins in innate immunity: From C-reactive protein to the long pentraxin PTX3. J Clin Immunol. 2008;28:1–13
  33. Suliman ME, Qureshi AR, Carrero JJ, et al. The long pentraxin PTX-3 in prevalent hemodialysis patients: Associations with comorbidities and mortality. QJM. 2008;101:397–405
  34. Suliman ME, Yilmaz MI, Carrero JJ, et al. Novel links between the long pentraxin 3, endothelial dysfunction, and albuminuria in early and advanced chronic kidney disease. Clin J Am Soc Nephrol. 2008;3:976–985
  35. Lang CH, Frost RA, Vary TC. Regulation of muscle protein synthesis during sepsis and inflammation. Am J Physiol Endocrinol Metab. 2007;293:E453–E459
  36. Meisel SR, Shapiro H, Radnay J, et al. Increased expression of neutrophil and monocyte adhesion molecules LFA-1 and Mac-1 and their ligand ICAM-1 and VLA-4 throughout the acute phase of myocardial infarction: Possible implications for leukocyte aggregation and microvascular plugging. J Am Coll Cardiol. 1998;31:120–125
  37. Kalantar-Zadeh K, Ikizler TA, Block G, Avram MM, Kopple JD. Malnutrition-inflammation complex syndrome in dialysis patients: Causes and consequences. Am J Kidney Dis. 2003;42:864–881
  38. Foley RN, Parfrey PS, Harnett JD, Kent GM, Murray DC, Barre PE. Hypoalbuminemia, cardiac morbidity, and mortality in end-stage renal disease. J Am Soc Nephrol. 1996;7:728–736
  39. Kalantar-Zadeh K, Kopple JD, Block G, Humphreys MH. A malnutrition-inflammation score is correlated with morbidity and mortality in maintenance hemodialysis patients. Am J Kidney Dis. 2001;38:1251–1263
  40. Cheema B, Abas H, Smith B, et al. Progressive Exercise for Anabolism in Kidney Disease (PEAK): A randomized, controlled trial of resistance training during hemodialysis. J Am Soc Nephrol. 2007;18:1594–1601
  41. Raj DS, Moseley P, Dominic EA, et al. Interleukin-6 modulates hepatic and muscle protein synthesis during hemodialysis. Kidney Int. 2008;73:1045–1061
  42. Shah V, Dominic EA, Moseley P, et al. Hemodialysis modulates gene expression profile in skeletal muscle. Am J Kidney Dis. 2006;48:616–628
  43. Ulrich C, Heine GH, Garcia P, et al. Increased expression of monocytic angiotensin-converting enzyme in dialysis patients with cardiovascular disease. Nephrol Dial Transplant. 2006;21:1596–1602
  44. Snaedal S, Heimburger O, Qureshi AR, et al. Comorbidity and acute clinical events as determinants of CRP variation in hemodialysis patients: Implications on patient survival. Am J Kidney Dis. 2009;53:1024–1033

 Originally published online as doi:10.1053/j.ajkd.2009.06.022 on September 7, 2009.

 D.S.C.R. and J.J.C. contributed equally to this work.

PII: S0272-6386(09)00940-8

doi:10.1053/j.ajkd.2009.06.022

Refers to article:

  • Soluble CD14 and Endotoxin Levels in Hemodialysis Patients: A Tale of 2 Molecules

    Victor F. Seabra, George Thomas, Bertrand L. Jaber
    American Journal of Kidney Diseases December 2009 (Vol. 54, Issue 6, Pages 990-992)

American Journal of Kidney Diseases
Volume 54, Issue 6 , Pages 1072-1080, December 2009

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