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NDT Advance Access originally published online on December 5, 2005
Nephrology Dialysis Transplantation 2006 21(3):677-682; doi:10.1093/ndt/gfi309
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© The Author [2005]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Original Articles: Clinical Nephrology

Advanced glycation end-product peptides are associated with impaired renal function, but not with biochemical markers of endothelial dysfunction and inflammation, in non-diabetic individuals

Frank Stam1,4, Casper G. Schalkwijk2,4,6,7, Coen van Guldener1,4,5, Piet M. ter Wee3,4 and Coen D. A. Stehouwer1,4,6,7

1 Department of Internal Medicine, 2 Department of Clinical Chemistry, 3 Department of Nephrology, 4 Institute for Cardiovascular Research, VU University Medical Centre, Amsterdam, 5 Department of Internal Medicine, Amphia Hospital (Langendijk), Breda, 6 Department of Internal Medicine, Academic Hospital Maastricht and 7 Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands

Correspondence and offprint requests to: Frank Stam, Department of Internal Medicine, VU University Medical Centre, PO Box 7057, 1007 MB Amsterdam, The Netherlands. Email: f.stam{at}vumc.nl



   Abstract
Top
 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. Patients with end-stage renal disease as well as mild renal impairment have an increased risk for the development of cardiovascular disease. It has been suggested that advanced glycation end-products (AGEs) are involved in atherogenesis, possibly through induction of endothelial dysfunction and low-grade inflammation.

Methods. In a cross-sectional, single-centre study, we investigated four groups of 20 non-diabetic subjects with a creatinine clearance ranging from normal (>90 ml/min/1.73 m2) to <31 ml/min/1.73 m2. We measured AGE-peptides, markers of endothelial dysfunction (von Willebrand factor, soluble E-selectin, plasminogen activator inhibitor-1, tissue-type plasminogen activator, soluble vascular cell adhesion molecule-1) and markers of inflammatory activity (soluble intercellular adhesion molecule-1, C-reactive protein, secretory phospholipase A2). We constructed composite endothelial dysfunction and inflammatory activity Z-scores using these markers.

Results. AGE-peptides were independently related to creatinine clearance (standardized ß –0.55, 95% confidence interval (CI) –0.77 to –0.34, P<0.001). AGE-peptides were not independently related to the individual markers of endothelial dysfunction and inflammation, nor to the composite endothelial dysfunction Z-score (standardized ß 0.08, 95% CI –0.14 to –0.30, P = 0.48) or the inflammatory activity Z-score (standardized ß –0.05, 95% CI –0.25 to –0.16, P = 0.66).

Conclusions. Plasma concentrations of AGE-peptides are associated with creatinine clearance but not with biochemical markers of endothelial dysfunction and inflammatory activity in non-diabetic patients over a wide range of renal function. This suggests that the atherogenic effects of AGE-peptides in individuals with renal functional impairment are not mediated by endothelial dysfunction or inflammatory activity as estimated by the markers used.

Keywords: advanced glycation end-products; cell adhesion molecules; chronic inflammation; creatinine clearance; endothelial dysfunction; von Willebrand factor



   Introduction
Top
 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 References
 
Patients with chronic kidney disease, end-stage renal disease as well as mild renal impairment, have an increased risk for the development of cardiovascular disease. Endothelial dysfunction and chronic low-grade inflammation may play a major role in atherogenesis and evidence accumulates that atherosclerosis may be an inflammatory disease, in which immune mechanisms interact with metabolic risk factors [1]. A high blood concentration of advanced glycation end-products (AGEs), a heterogeneous group of compounds, derived from the non-enzymatic reaction between glucose or other reducing sugars and proteins, has been suggested to be one of these metabolic factors [2].

AGEs may be involved in atherogenesis by interacting with specific receptors for AGE, which leads to the production of free oxygen radicals and subsequent release of cytokines [3]. In addition, AGEs have been found to accumulate in the vascular matrix where they are thought to disturb endothelial permeability and induce vessel-wall thickening [2]. Accumulation of AGEs in plasma has been described in diabetic and non-diabetic patients with end-stage renal disease [4]. Information about the relationship between creatinine clearance and AGEs in non-diabetic individuals with predialysis renal dysfunction is scarce and mainly derived from patients after kidney transplantation, where blood concentrations of AGEs normalized when normalization of renal function was achieved after kidney transplantation [5].

Resistance to complete enzymatic degradation of AGE-modified proteins leads to the formation of AGE-peptides. Measurement of AGE-peptides can be easily performed by a simple analytical procedure using spectrophotometry and spectrofluoroscopy as first described by Wróbel et al. [6]. Age-peptides have been shown to be related to renal function in diabetic patients with chronic kidney disease [7] and non-diabetic patients after kidney transplantation [5].

In the present study, we investigated the relationship between renal function, as estimated by the Cockcroft–Gault creatinine clearance, and AGE-peptides in non-diabetic individuals with a wide range of renal function. In addition, we aimed to investigate whether AGE-peptides were associated with biochemical markers of endothelial dysfunction and inflammatory activity.



   Subjects and methods
Top
 Abstract
 Introduction
 Subjects and methods
Results
 Discussion
 References
 
Subjects
The study population has been previously described [8]. Briefly, 80 consecutive patients were recruited from the outpatient clinics of the Departments of Nephrology and Internal Medicine of the VU University Medical Centre. Exclusion criteria were age under 18 years or over 75 years, haemodialysis, peritoneal dialysis, renal transplantation, diabetes mellitus (ADA criteria), inflammatory diseases, WHO performance greater than 2, severe other disease (malignancy or liver disease) or use of folic acid, immunosuppressive drugs, penicillamine or anticonvulsant drugs. Patients were included until four groups of 20 subjects were formed with a creatinine clearance (calculated with the formula of Cockcroft and Gault) of 91 ml/min or higher, 61–90 ml/min, 31–60 ml/min and less than 31 ml/min/1.73 m2. This was done to assure a balanced representation throughout the whole spectrum of renal function. After correcting the creatinine clearance for body surface area, the group was divided into quartiles. In 65 (81%) of the 80 subjects a renal disease was diagnosed: hypertensive nephrosclerosis in 20, polycystic kidney disease in 15, primary glomerular disease in 14, urolithiasis in four, non-active vasculitis in four, chronic pyelonephritis in two, Alport syndrome in two and other renal diseases in four. Most of the 15 (19%) patients without renal disease were evaluated for chronic fatigue or treated for thyroidal illness. Of these 15 patients without renal disease 10 were included in the control group and five in the group with a creatinine clearance between 61 and 90 ml/min. Of each patient, data were collected with regard to age, cardiovascular medication (antihypertensive medication, platelet aggregation inhibitors and lipid-lowering drugs), smoking status (having smoked in the past year), presence of cardiovascular disease (history of myocardial infarction, angina pectoris, stroke or peripheral arterial occlusive disease), body mass index and systolic and diastolic blood pressure (the mean of three measurements during one visit, performed with a mercury sphygmanometer at the left arm, with the individual seated). The presence of hypertension was defined as a systolic blood pressure >140 mmHg, a diastolic blood pressure >90 mmHg and/or use of antihypertensive medication. Hypercholesterolaemia was defined as a serum total cholesterol level >5.0 mmol/l and/or the use of lipid-lowering medication. Blood samples were taken in the fasting state. Plasma was immediately separated and frozen at –20°C for homocysteine and at –70°C for AGEs and markers of endothelial dysfunction and inflammation, until analysis.

The protocol was approved by the ethics committee of the VU University Medical Centre and all patients gave their informed consent.

Measurement of advanced glycation end-product-peptides
AGE-peptides were measured with a simple analytical procedure as described by Wróbel et al. [6] based on simultaneous detection of low-molecular-mass peptides and AGE-peptides with a flow system and two detectors connected online: spectrophotometrically for peptides (absorption at 280 nm) and spectrofluorometrically for AGE-peptides (ex = 247 nm, em = 440 nm). Briefly, plasma (40 µl) in microcentrifuge tubes was deproteinized with trichloroacetic acid (460 µl, 0.15 mol/l) and lipids were simultaneously extracted with chloroform (100 µl). The tubes were shaken vigorously and were centrifuged (10 min x 12000 g). Twenty µl of the aqueous layer was injected and fluorescence and absorption signals were measured. The ratio between fluorescence and absorption signal was calculated. AGE-peptide concentrations were determined with a proteinase K digest of AGE–bovine serum albumin (BSA) as calibrator (100% AGE-peptide calibrator). AGE–BSA was prepared by incubating BSA (50 g/l) with 0.5 mol/l glucose in 0.2 mol/l phosphate buffer (pH 7.4) for 42 days. After incubation, dialysis against phosphate buffered saline was carried out to remove unbound material. The AGE peptide calibrator was obtained by hydrolysis of AGE–BSA (50 g/l) with proteinase K: 10 µl of proteinase K solution (8 g/l) was mixed with 90 µl of AGE–BSA and incubated for 24 h at 37°C. In parallel, BSA was incubated with proteinase K to obtain a peptide calibrator (0% AGE-peptide calibrator). Mean AGE-peptide levels (±SD) in 44 healthy subjects were 10.6±1.7% (of the difference in AGE-peptide concentration between the 100 and 0% AGE-peptide calibrator), which is comparable with the AGE-peptides amounts measured in healthy subjects by Wróbel et al. [6]. Within-day and between-day coefficients of variation were <3% at an AGE-peptide concentration corresponding to that in healthy subjects.

Other measurements
We determined plasma concentrations of von Willebrand factor (vWf), soluble vascular-cell adhesion molecule-1 (sVCAM-1), soluble E-selectin (sE-selectin), tissue-type plasminogen activator (tPA) and plasminogen activator inhibitor-1 (PAI-1) as markers of endothelial dysfunction, and soluble intercellular adhesion molecule-1 (sICAM-1), C-reactive protein (CRP) and secretory phospholipase A2 (sPLA2) as markers of inflammatory activity. All markers were measured in duplicate. In addition, plasma total (free plus protein bound) homocysteine (tHcy) and total cholesterol, serum creatinine and urinary levels of creatinine and protein were determined. All measurement techniques have been described previously elsewhere [8].

Statistical analysis
All analyses were performed with SPSS, version 11.5 (SPSS Inc, Chicago, IL, USA). Variables are presented as mean±SD, number with percentage of total, or, in case of a skewed distribution, median with interquartile range. Analysis of variance (ANOVA) was used to test differences between groups. Pearson's test was used to assess bivariate correlations. To study whether AGE-peptides were related to creatinine clearance, body mass index, blood pressure, proteinuria and blood levels of total cholesterol, total homocysteine and markers of endothelial dysfunction and inflammatory activity, all regression analyses were performed with adjustment for age. In addition, to explore whether AGE-peptides were independently related to creatinine clearance, markers of endothelial dysfunction and markers of inflammatory activity, regression analyses were performed with five additional models. In the first model, multivariate analysis was performed with adjustment for age, sex, body mass index, diastolic blood pressure, the presence of cardiovascular disease and smoking status. In models 2–5, sequential adjustments were performed for plasma total cholesterol, tHcy, and estimates of endothelial dysfunction and inflammatory activity, respectively. When necessary, variables were log-transformed for a better fit in linear regression analyses.

Because markers of endothelial dysfunction and inflammatory activity show marked intra-individual (day-to-day) variation and because we measured these markers only once, the associations (if any) of endothelial dysfunction and inflammatory activity with other variables will tend to be underestimated. Therefore, we created mean SD (Z-)scores for markers of endothelial dysfunction and inflammatory activity, and used these in regression analyses as described in the following. For every individual, each variable was expressed as SDs of difference from the population mean. The mean Z-scores were calculated as the mean of these SD scores as follows: endothelial dysfunction Z-score = (vWf + sVCAM-1 + sE-selectin + PAI-1 + tPA)/5, and inflammatory activity Z-score = (CRP + sICAM-1 + sPLA2)/3. Thus, high scores reflect high levels of endothelial dysfunction and inflammatory activity, respectively.

A P-value <0.05 was considered to reflect statistical significance.



   Results
Top
 Abstract
 Introduction
 Subjects and methods
 Results
Discussion
 References
 
Table 1 shows baseline characteristics of the participants according to quartiles of creatinine clearance.


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  		Table 1. Baseline characteristicsa

 
Figure 1 shows the significant inverse relationship between AGE-peptides and creatinine clearance. The age-adjusted relations between AGE-peptides and (potential) risk factors for cardiovascular disease are presented in Table 2. Age itself did not significantly correlate with AGE-peptides (r = 0.19, P = 0.10).


Figure 1
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  		Fig. 1. Relation between the natural logarithm of the plasma concentration of advanced glycation end-product-peptides and creatinine clearance (n = 80). Pearson's correlation coefficient: –0.59 (P<0.001).

 

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  		Table 2. Relation between advanced glycation end-product-peptides and risk factors for cardiovascular disease

 
Multivariate analyses (Table 3) showed that, after adjustment for age, sex, body mass index, diastolic blood pressure, prior cardiovascular disease and smoking, creatinine clearance was independently associated with AGE-peptides. Sequential addition of total cholesterol, plasma tHcy, endothelial dysfunction score and plasma inflammatory activity score did not materially change this relationship. Besides creatinine clearance, none of the independent variables was significantly associated with AGE-peptides. When, in models 4 and 5, adjustment for the separate (instead of the Z-scores) markers for endothelial dysfunction and inflammation was performed, the relationship between creatinine clearance and AGE-peptides was also not materially affected (data not shown). AGE-peptides were not independently related to vWf (standardized ß –0.04, 95% CI –0.25 to 0.18, P = 0.74), sE-selectin (standardized ß 0.02, 95% CI –0.17 to 0.21, P = 0.81), PAI-1 (standardized ß 0.15, 95% CI –0.06 to 0.35, P-value 0.16), tPA (standardized ß 0.08, 95% CI –0.12 to 0.27, P = 0.45), sVCAM-1 (standardized ß –0.01, 95% CI –0.17 to 0.16, P = 0.95), or the endothelial dysfunction Z-score (standardized ß 0.08, 95% CI –0.14 to 0.30, P = 0.48). Nor were AGE-peptides significantly related to sICAM-1 (standardized ß 0.05, 95% CI –0.15 to 0.26, P-value 0.62), CRP (standardized ß –0.12, 95% CI –0.29 to 0.06, P-value 0.23) and sPLA2 (standardized ß –0.02, 95% CI –0.22 to 0.18, P-value 0.84), or to the inflammatory activity Z-score (standardized ß –0.05, 95% CI –0.25 to 0.16, P = 0.66).


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  		Table 3. Multiple regression analysis of the relation between advanced glycation end-product-peptides and creatinine clearance

 
Additional analysis
As age, sex, body weight and height are part of the formula for calculation of the body surface adjusted creatinine clearance, all models were tested without these variables. This did not materially influence our results. For example, in models 4 and 5, the standardized ßs of the relations between creatinine clearance and AGE-peptides, without adjustment for sex, age, and body mass index, were –0.45 (95% CI –0.66 to –0.23, P<0.001) and –0.46 (95% CI –0.68 to 0.25, P<0.001), respectively (other data not shown).



   Discussion
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
References
 
This study shows that plasma concentrations of AGE-peptides were independently related to creatinine clearance in non-diabetic individuals over a wide range of renal function. AGE-peptides were not independently related to endothelial dysfunction and inflammatory activity, as estimated by a panel of markers.

The relation between renal function on the one hand and AGEs as well as AGE-peptides on the other has been mainly investigated and demonstrated in patients with diabetes mellitus [9], end-stage renal disease [10] and after kidney transplantation [5]. Sharp et al. [7] found a positive relationship between serum creatinine and AGE-peptides in 106 healthy individuals with an apparently normal renal function (median serum creatinine 90 µmol/l, range 42–150 µmol/l). The present study, using a more accurate assessment of renal function, confirms this relationship in the full range from normal to predialysis renal function. The most likely mechanism for the accumulation of AGEs and AGE-peptides seems to be a decreased renal excretion [11], although contribution of a disturbed elimination of AGEs in the liver [12] or increased de novo generation of AGEs [13] cannot be excluded.

The relation between AGEs (or AGE-modified peptides) and cardiovascular complications is still under examination. The widespread belief that AGEs contribute to the development of cardiovascular disease [2] was initially based on animal studies that demonstrated properties of AGEs to induce vasoconstriction, complement activation, cytokine release, procoagulant effects and oxidative stress [3]. Furthermore, in a study in haemodialysis patients, alterations in left ventricular geometry were independently related to plasma concentration of the AGE-pentosidine [14]. Clinical trials with inhibitors of AGE-formation (aminoguanidine) and cross-link breakers (ALT-711) have confirmed the potential role of AGEs in the development of vascular complications in diabetic patients [15]. So far, however, prospective studies in patients with chronic kidney disease and/or diabetes have not been able to link high AGEs to cardiovascular morbidity and mortality [10].

We did not find an independent relationship between blood levels of high serum AGE-peptides and biomarkers of endothelial dysfunction and inflammatory activity. With respect to endothelial dysfunction, in vitro studies have shown that exposure of endothelial cells to AGEs enhances vascular expression of sVCAM-1 and sE-selectin [16]. In diabetic patients, high serum AGEs (the major AGEs N{epsilon}-(carboxymethyl)lysine (CML) and N{epsilon}-(carboxyethyl)lysine (CEL)) were associated with high plasma levels of sVCAM-1, vWf and soluble thrombomodulin [9]. An association between high serum AGEs and impaired endothelium-dependent vasodilatation could be demonstrated in diabetic patients [17], which was not the case in end-stage renal disease [18].

With respect to inflammatory activity, expression of the receptor for AGE on peripheral blood monocytes has been shown to be associated with plasma levels of CRP and tumour necrosis factor alpha in patients with chronic kidney disease [19]. However, as in this study, a relationship between blood levels of AGE-peptides and CRP could also not be demonstrated in patients with end-stage renal disease [10] and diabetes [9].

This study has some limitations. The use of the AGE-peptides as reflection of AGEs in plasma requires some discussion. Several AGEs, such as argpyrimidine and pentosidine, exhibit characteristic fluorescence. Based on this, a novel simple analytical procedure to measure AGE-peptides with on-line spectrophotometric and spectrofluorometric detection was developed [6]. This technique has been validated with an AGE-Elisa [6], and we demonstrated a strong correlation of AGE-peptides with the well-characterized non-fluorescent AGEs CML and CEL, indicating the specificity of this technique for the quantification of AGEs [20]. However, the fluorophores as determined in this assay are unknown and the exact specificity of the assay needs to be further determined.

In addition, due to the limited number of patients and the variety of renal diseases, the possibility of a relationship between AGE-peptides and markers of endothelial function and inflammatory activity cannot be unequivocally excluded, especially in subgroups. The intra-individual variability of the markers of endothelial function and inflammatory activity was not assessed in this study, but the use of a composite Z-score of these markers should have lessened a masking effect (if any) on the associations that were studied. Of course, the cross-sectional nature of this study does not allow conclusions on the relationship between renal and cardiovascular outcomes.

In conclusion, plasma concentrations of AGE-peptides are associated with creatinine clearance but not with biochemical markers of endothelial dysfunction and inflammatory activity in non-diabetic patients with a wide range of predialysis renal function. Therefore, the supposed atherogenic effect of AGEs seems not to be mediated by endothelial dysfunction or chronic low-grade inflammation, as reflected by vWf, sVCAM-1, sE-selectin, PAI-1 and tPA, and CRP, sICAM-1 and sPLA2, respectively. Thus, this study does not support the use of these biomarkers of endothelial dysfunction and inflammatory activity as intermediary end points of AGE-peptide-reducing interventions aiming for cardiovascular risk reduction.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 8. 8.05
Accepted in revised form: 11.11.05


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