Sage Journals: Discover world-class research

Abstract

Systemic vascular changes contribute to both the pathogenesis and thrombotic comorbidities of end-stage renal disease (ESRD). This study aims to profile various biomarkers and better understand their role in the pathogenesis of ESRD. Plasma samples from 49 patients with ESRD and 56 control individuals were analyzed for markers for inflammation, specifically C-reactive protein (CRP), tumor necrosis factor receptor 1 (TNFR1), neutrophil gelatinase-associated lipocalin (NGAL); thrombomodulin (TM); neuron-specific enolase (NSE), and thrombosis-D-dimer (DD). Compared to controls, all markers studied showed a statistically significant upregulation in patients with ESRD. These results indicate a polypathologic process in patients with ESRD, leading to cardiovascular and cerebrovascular events. However, the clinical significance of previously untested markers, such as TNFR1, NGAL, and NSE, still needs to be further explored. This study further validates the role of endothelial damage and endogenous thrombotic processes in ESRD as evidenced by the increased levels of TM and DD.

Keywords

ESRD biomarker NGAL NSE

Introduction

Atherosclerosis accounts for over 60% of mortality in chronic renal failure (CRF).^1–3 This includes both cardiovascular and cerebrovascular comorbidities. Inflammation is known to be a factor in atherosclerosis and its thromboembolic sequelae. Leukocytosis, as well as other markers of inflammation, has been shown to be a risk factor for initial cardiovascular and cerebrovascular events,⁴ as well as recurrent events.⁵ Inflammatory markers are predictors of mortality from these thromboembolic events.⁶

Leukocytes promote atherosclerotic changes via their activation and production of inflammatory mediators. These substances then cause changes in the vascular endothelium, platelets, and other circulating substances that initiate molecule adhesion and coagulation.⁷ There are many systemic diseases that lead to end-stage renal disease (ESRD), for example diabetes, hypertension, and autoimmune diseases such as lupus. An inflammatory state has been associated with all these systemic diseases and ESRD,¹ but the profiling of several mediators such as neuron-specific enolase (NSE), tumor necrosis factor receptor 1 (TNFR1), D-dimer (DD), and thrombomodulin (TM) has not been reported. It is postulated that since ESRD involves vascular dysfunction, markers of endothelial origin such as TM and TNFR1 will be elevated. Similarly, endothelial damage should result in tissue factor release and activation of coagulation, resulting in elevated DD levels. Previous studies have reported elevation of C-reactive protein (CRP) and neutrophil gelatinase-associated lipocalin (NGAL) in patients with ESRD^1,8 and our study will attempt to confirm these findings.

C-Reactive Protein

C-reactive protein is a member of pentraxin family of proteins with an approximate molecular mass of 118000 kDa.⁹ It is an acute-phase reactant whose synthesis in the liver is regulated by interleukin-6 and other inflammatory cytokines.¹⁰ C-reactive protein is known to be elevated in patients with CRF, especially patients on dialysis,^1,11 and also been shown to be positively associated with both ischemic heart disease¹² and cerebrovascular disease.¹³

Neutrophil Gelatinase-Associated Lipocalin

Neutrophil gelatinase-associated lipocalin is a 25-kDa member of the lipocalin protein family, which is secreted from specific granules of neutrophils.^8,14 Upregulation of NGAL expression is thought to be the result of interactions between inflammatory cells and the vascular endothelium.¹⁵ Studies looking at NGAL expression in various human tissues postulate that NGAL may play a role in apoptosis.¹⁶

It has also been suggested that NGAL may represent a biomarker of early ischemic renal injury, both in terms of kidney damage as well as endothelial activation, which would be applicable in ESRD.¹⁷ Other studies demonstrate that exogenous NGAL in early renal injury decreases cell death.¹⁸ Several studies report that upregulation of NGAL is predictive of severity of injury in acute renal failure.¹⁹ One study has shown that NGAL is positively correlated with progression of chronic kidney disease (CKD).²⁰ However, limited data is available on its role in ESRD and its association with ESRD complications.

Soluble TNF-α Receptor1

Tumor necrosis factor receptor 1 is a soluble form of the TNF receptor I which represents the extracellular domain of the protein. Tumor necrosis factor receptor 1 is released into the circulating plasma during inflammation. Tumor necrosis factor α is known to be elevated in chronic renal failure.¹ It is also associated with increased risk of myocardial infarction and death due to an MI.²¹ Some studies suggest that TNF receptors may actually be better plasma markers than TNF-α alone.²²

Neuron Specific Enolase

Neuron-specific enolase, an isozyme of enolase, is a dimeric glycolytic enzyme that converts 2-phosphoglycerate to phosphoenolpyruvate.²³ It is a tumor marker of neuroendocrine and neuronal origin, and thus is a useful marker for neuronal damage of various etiologies, including cerebrovascular disorders such as stroke.²⁴ It has been noted that NSE levels in the serum correlate with cerebrospinal fluid (CSF) levels, as well as the amount of infarcted tissue and duration of ischemia in patients with stroke.^25,26

D-Dimer

D-dimer is a degradation product of fibrin found in thrombotic states. Fibrin polymers are cross-linked to form a stable clot. When cross-linked fibrin is degraded by plasmin, the DD antigen becomes exposed. D-dimer has not only been used to assess patients for active thrombosis, but has recently been proposed as a marker for risk of recurrent thrombosis.²⁷

Thrombomodulin

Thrombomodulin is an endothelial protein that converts circulating plasma protein C into an active protease. Activated protein C is important in maintaining anticoagulation via the breakdown of activated clotting factors. Thrombomodulin also binds to thrombin which inhibits thrombin’s procoagulant effect. Thrombomodulin is present in the endothelium of vessels in all human tissues, excluding the brain.^28,29 It has been well documented that TM is released during endothelial damage in diseases such as stroke and MI.³⁰ A soluble form has also been isolated from human plasma and urine.³¹

Objectives

The purpose of this study is to profile the aforementioned analytes in patients with ESRD compared to a group of normal individuals. This information will be of interest in understanding of the pathophysiology of ESRD and its propensity for thromboembolic complications. It may also help to risk stratify patients with regard to complications of ESRD and have an impact on improving therapeutic approaches.

While most of these assays are commonly carried out separately utilizing ELISA-based methods, a new biochip-array technology is used to profile the markers of these patients. With the introduction of this biochip-array, it is possible to simultaneously measure multiple markers from a single patient, using only a small amount of plasma. This will have implications on the practical aspect of biomarker profiling in the future.

Materials and Methods

Sample Collection

Forty-nine patients with ESRD who undergo dialysis three times per week at an outpatient facility were selected for this study after informed consent. This study was approved by the Loyola University Internal Review Board for human participants. Plasma samples were collected in citrated tubes from each patient prior to hemodialysis. Control samples were also collected from 56 volunteers with no known kidney disease in the same fashion. Each sample was centrifuged at 3000 rpm for 20 minutes, and then stored at –70°C until the samples were analyzed.

Biomarker Analysis

All samples were analyzed using the Randox Evidence Investigator, which is a recently developed biochip array technology that utilizes a chip containing multiple discrete test regions of immobilized antibody to simultaneously quantify multiple markers from a small quantity of patient plasma (Randox Laboratories Ltd, Crumlin, United Kingdom). The Randox system offers a unique approach for the profiling of inflammatory and hemostatic markers. This system uses a chemiluminescent assay based on the light signal generated from each test region of the biochip, which is captured by a camera and analyzed using digital imaging technology. The signal is then compared to a calibrator constructed for each parameter. Each sample was run on the CRB II biochip according to the Randox protocol. The chips were imaged utilizing the Randox Evidence Investigator and raw data for the concentration of each analyte were obtained.

Statistical Analysis

Levels of each marker were collected for both patients with ESRD and control samples. Mean, range, standard deviation, and standard error of the mean were calculated. The data was then statistically analyzed using a 2-tailed Mann-Whitney U test with Gaussian approximation. This yielded a P value and 95% confidence interval for each variable.

Results

All 6 markers (TNFR1, TM, NGAL, NSE, CRP, and DD) showed an upregulation in ESRD compared to the control group. Table 1 shows the data obtained for each marker in both the ESRD group (left column) and the control group (middle column). The comparison between groups and its statistical significance is shown in the right-hand column. In Figure 1 , the mean for each marker is graphed, with the error bars representing standard error of the mean.

Table 1.

Various Marker Levels in ESRD and Control Patients

Marker	Control			ESRD			P	% Δ	Fold Δ
Marker	Mean	SD	95% CI	Mean	SD	95% CI	P	% Δ	Fold Δ
CRP (μg/mL)	1.38	±1.67	0.92-1.84	5.71	±4.15	4.52-6.90	<.001	315	4.1
DD (ng/mL)	107	±161	64.5-150	319	±204	262-376	<.001	197	3
NSE (ng/mL)	3.65	±4.34	2.50-4.80	6.61	±5.80	4.93-8.31	<.001	81	1.8
NGAL (ng/mL)	299	±100	273-325	1390	±257	1318-1462	<.001	364	4.6
TNFR1 (ng/mL)	0.39	±0.20	0.34-044	7.79	±2.78	7.01-8.57	<.001	1885	19.8
TM (ng/mL)	1.24	±0.40	1.14-1.34	6.45	±2.61	5.72-7.18	<.001	422	5.2

Abbreviations: DD, D-dimer; ESRD, end-stage renal disease; Fold Δ, fold increase of ESRD vs control; NSE, neuron-specific enolase; NGAL, neutrophil gelatinase-associated lipocalin; SD, standard deviation; P, P value for the difference between ESRD and control groups; % Δ, percentage difference between control vs ESRD; TM, thrombomodulin; TNFR1, tumor necrosis factor receptor 1.

Figure 1.

Inflammatory marker levels in end-stage renal disease (ESRD) and control. The mean for the concentration of each marker level in both ESRD and control patients (numerical values shown) is demonstrated. The error bar represents the standard error of the mean. The most upregulation is seen in tumor necrosis factor receptor 1 (TNFR1), thrombomodulin (TM) and neutrophil gelatinase-associated lipocalin (NGAL).

Tumor necrosis factor receptor 1 showed the greatest difference compared to the control group with a 19.8-fold increase. The value for each patient sample, both ESRD and control, is represented as scatter points in Figure 2 . The ovals represent grouping of scatter to denote a cluster and are generated using Microsoft Excel software. There was a wide range of values obtained in the patients ESRD (0.77 to 13.67). In addition, the control group exhibited both very low levels and a narrow range of values (0.0 to 0.99).

Figure 2.

TNF Receptor 1 Concentration in end-stage renal disease (ESRD) and control. The vertical axis plots the concentration of tumor necrosis factor receptor 1 (TNF1) in both ESRD and control patients. Each patient sample is plotted randomly along the horizontal axis. Ovals represent the area of the mean ± standard deviation. Clear upregulaiton of TNFRI is seen here with heterogeneity among patients with ESRD, but also with distinct separation from the control group.

Thrombomodulin and NGAL were also increased 5.2-fold and 4.6-fold, respectively (Table 1). Similar to TNFR1, individual TM levels were quite heterogeneous among the patients with ESRD (Figure 3 ), with levels ranging from 0.73 to 14.09 ng/mL. However, NGAL was more variable among the control group (115 to 603) and less so among the ESRD group (406 to 1729).

Figure 3.

Thrombomodulin concentration in end-stage renal disease (ESRD) and control. The vertical axis plots the concentration of thrombomodulin in both ESRD and control patients. Each patient sample is plotted randomly along the horizontal axis. Ovals represent the area of the mean ± standard deviation. Clear upregulaiton of thrombomodulin is seen with heterogeneity among patients with ESRD.

C-reactive protein, DD, and NSE were increased 4.2-, 3.0-, and 1.8-fold, respectively (Table 1). These values also achieved statistical significance. However, there was drastically more overlap seen between the ESRD and control values in CRP, DD, and NSE compared to TNFR1, TM, and NGAL. Despite the heterogeneity of individual values in CRP and DD, the mean ± the standard deviation of these markers shows a significant difference between the ESRD and control groups. Although the data for NSE yielded a statistically significant result for the difference between ESRD and control patients, there was marked overlap between the groups, with the 95% confidence intervals being 2.5 to 4.8 and 4.9 to 8.3 ng/mL, respectively.

Discussion

This study shows that TNFR1 is the most profoundly elevated plasma marker of inflammation compared to the other markers analyzed in this study. This study has identified TNFR1 as a promising marker for future studies involving ESRD, dialysis patients, and thromboembolic complications of ESRD. Given the degree of elevation of TNFR1 and its known association with myocardial infarctions,²¹ this marker has the potential to provide a means of risk-stratifying patients with regard to thromboembolic outcomes.

In addition, TM and NGAL showed upregulation of a high statistical significance. Much like TNFR1, these markers showed pronounced separation from the control values. Furthermore, these markers exhibited heterogeneity, which if correlated with comorbidities and patient outcomes, could also provide a means of risk-stratifying ESRD patients. However, this heterogeneity could also be explained by individual patient variance and disease progression.

Given the upregulation of all 6 inflammatory markers, these results are highly suggestive of a multifactorial pathophysiology for ESRD. The origins of the markers utilized in this study imply the involvement of leukocytes, platelets, endothelial cells, and other tissues in the generation of inflammatory mediators. The elevation of TNFR1 is likely due to a state of increased cellular damage and release of the receptor from the cell membranes. Similarly, TM and DD levels validate the role of endothelial damage and endogenous thrombotic processes in ESRD. However, the interplay between these mediators, and the significance of previous unstudied markers such as NGAL, require further investigation. These results should also be correlated with patient outcomes over time to determine whether the statistically significant marker levels, in fact, has some clinical implication.

The biochip-array technology utilized in this study proved to be a useful method for the simultaneous quantification of NSE, NGAL, TNFR1, DD, TM, and CRP. It allowed for 6 different assays to be performed on a small amount, less than 1 mL, of citrated plasma sample. In addition, the biochip-array required much less time to complete than a standard ELISA method, since all 6 reactions were run simultaneously.

There were several limitations to this study. The sample size of the patients with ESRD and the controls was small. Although these groups provided statistical significance for all of the markers studied, larger groups may help establish a better baseline given the heterogeneity of values for several of the markers. In addition, a control group that is matched to the ESRD group for variables which effect inflammatory markers, such as BMI, smoking, age, and gender, would help give these numbers more validity. Furthermore, the ESRD patient samples were collected at a single point in time and are not controlled for time since diagnosis or time since initiation of dialysis. It is currently unknown what effect, if any, this would have on the degree of marker elevation. Future directions of this study include analyzing the correlation of these biomarkers with thromboembolic endpoints and the time to such events.

Conclusions

Our studies indicate that the pathogenesis of ESRD is complex and not yet fully understood. A mulitparametric analysis of unique biomarkers such as TNFR1, NGAL, and TM along with other mediators will be useful in understanding the mechanisms of ESRD and work toward risk-stratification of patients with ESRD. Furthermore, this information will also be valuable in developing therapeutic interventions.

Footnotes

Oral Presentation of this study was done at the National Student Research Forum, April 23, 2010, Galveston, TX, USA.

Acknowledgments

This research investigation was carried out as an adjunct to a doctorate in medicine with honors in research degree. The author would like to express gratitude toward Dr L Brubaker and Dr R Kennedy for their guidance and mentorship.

The authors declared no conflicts of interest with respect to the authorship and/or publication of this article.

The authors received no financial support for the research and/or authorship of this article.

References

Bolton

Downs

Victory

. Endothelial dysfunction in chronic renal failure: roles of lipoprotein oxidation and pro-inflammatory cytokines. Nephrol Dial Transplant. 2001;16(6):1189–1197.

Levey

Beto

Coronado

. Controlling the epidemic of cardiovascular disease in chronic renal disease: what do we do now? What do we need to learn? Where do we go from here?. Am J Kidney Dis. 1999;34(10):438–444.

USRDS (U.S. Renal Data System) 2009. Annual Data Report: Atlas of End Stage Renal Disease in the United States. Bethesda, MD: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2009.

Elkind

Cheng

Boden-Albala

. Tumor necrosis factor receptor levels are associated with carotid atherosclerosis. Stroke. 2002;33(1):31–37.

Biasucci

Liuzzo

Altamura

. Increasing levels of interleukin (IL)-1Ra and IL-6 during the first 2 days of hospitalization in unstable angina are associated with increased risk of in-hospital coronary events. Circulation. 1999;99(16):2079–2084.

Shlant

Forman

Stamler

. The natural history of coronary heart disease: prognostic factors after recovery from myocardial infarction in 2,789 men. Circulation. 1985;54(3):700–703.

Osterud

. A global view of the role of monocytes and platelets in atherogenesis. Thromb Res. 1997;85(1):1–22.

Venge

. Lipocalins as biochemical markers of disease. Biochim Biophys Acta. 2000;1482(1-2):298–307.

Ledue

Rifai

. Preanalytic and analytic sources of variations in C–reactive protein measurement: implications for cardiovascular disease risk assessment. Clin Chem. 2003;49(8):1258–1271.

10.

Castell

Gomez-Lechon

Davis

Fabra

Trullenque

Heinrich

. Acute-phase response of human hepatocytes: regulation of acute-phase protein synthesis by interleukin-6. Hepatology. 1990;12(5):1179–1186.

11.

Irish

. Cardiovascular disease, fibrinogen and the acute phase response associations with lipids and blood pressure in patients with chronic renal disease. Atherosclerosis. 1998;137(1):133–139.

12.

Koenig

Sund

Frohlich

. C-reactive protein, a sensitive marker of inflammation predicts future risk of coronary heart disease in initially healthy middle-aged men. Circulation. 1999;99(2):237–242.

13.

Cao

Thach

Manolio

. C-reactive protein, carotid intima-media thickness, and incidence of ischemic stroke in the elderly: the cardiovascular health study. Circulation. 2003;108(2):166–170.

14.

Carlson

Engstrom

Garcia

Peterson

Venge

. Purification and characterization of a human neutrophil lipocalin (HNL) from the secondary granules of human neutrophils. Scand J Clin Lab Invest. 1994;54(5):365–376.

15.

Mishra

Prada

. Identification of neutrophil gelatinase-associated lipocalin as a novel early urinary biomarker for ischemic renal injury. J Am Soc Nephrol. 2003;14(10):2534–2543.

16.

Devireddy

Teodoro

Richard

Green

. Induction of apoptosis by a secreted lipocalin that is transcriptionally regulated by IL-3 deprivation. Science. 2001;293(5531):829–834.

17.

Yang

Goetz

J-Y

. An iron delivery pathway mediated by a lipocalin. Mol Cell. 2002;10(5):1045–1056.

18.

Mori

Lee

Rapoport

. Endocytic delivery of lipocalin-siderophore-iron complex rescues the kidney from ischemia-reperfusion injury. J Clin Invest. 2005;115(3):610–621.

19.

Mishra

Mori

Kelly

Barasch

Devarajan

. Neutrophil gelatinase-associated lipocalin: a novel early urinary biomarker for cisplatin nephrotoxicity. Am J Nephrol. 2004;24(3):307–315.

20.

Bolignano

Lacquaniti

Coppolino

. Neutrophil gelatinase-associated lipocalin and progression of chronic kidney disease. Clin J Am Soc Nephrol. 2009;4(2):337–344.

21.

Ridker

Rifai

Pfeffer

Sacks

Lepage

Braunwald

. Elevation of tumor necrosis factor-α and increased risk of recurrent coronary events after myocardial infarction. Circulation. 2000;101(18):2149–2153.

22.

Blann

McCollum

. Increased levels of soluble tumor necrosis factor receptors in atherosclerosis: no clear relationship with levels of tumor necrosis factor. Inflammation. 1998;22(5):483–491.

23.

Cunningham

Watt

Winder

. Serum neuron-specific enolase as an indicator of stroke volume. Eur J Clin Invest. 1996;26(4):298–303.

24.

Marangos

Schmechel

. Neuron specific enolase, a clinically useful marker for neurons and neuroendocrine cells. Annu Rev Neurosci. 1987;10(1):269–295.

25.

Steinberg

Gueniau

Scarna

Keller

Worcel

Pujol

. Experimental brain ischemia; neurone-specific enolase level in cerebrospinal fluid as an index of neuronal damage. J Neurochem. 1984;43(1):19–24.

26.

Hay

Royds

Davies-Jones

. Cerebrospinal fluid enolase in stroke. J Neurol Neurosurg. 1984;47(1):724–729.

27.

Palareti

Cosmi

Legnani

. D-dimer testing to determine the duration of anticoagulation therapy. N Engl J Med. 2006;355(17):1780–1789.

28.

Maruyama

Bell

Majerus

. Thrombomodulin is found in endothelium of arteries, veins, capillaries, lymphatics, and on syncytiotrophoblast of human placenta. J Cell Biol. 1985;101(2):363–371.

29.

Ishii

Salem

Bell

Laposata

Majerus

. Thrombomodulin, an endothelial anticoagulant protein, is absent from human brain. Blood. 1985;101(5):363–367.

30.

Kozuka

Kohriyama

Nomura

Ikeda

Kajikawa

Nakamura

. Endothelial markers and adhesion molecules in acute ischemic stroke—sequential change and differences in stroke subtype. Atherosclerosis. 2002;161(1):161–168.

31.

Ishii

Majerus

. Thrombomodulin is present in human plasma and urine. J Clin Invest. 1985;76(6):2178–2181.

Upregulation of Inflammatory Mediators in End-Stage Renal Disease as Measured Using Biochip Array Technology

Abstract

Keywords

Introduction

C-Reactive Protein

Neutrophil Gelatinase-Associated Lipocalin

Soluble TNF-α Receptor1

Neuron Specific Enolase

D-Dimer

Thrombomodulin

Objectives

Materials and Methods

Sample Collection

Biomarker Analysis

Statistical Analysis

Results

Discussion

Conclusions

Footnotes

Acknowledgments

References