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NDT Advance Access first published online on June 5, 2007
This version published online on July 15, 2007
Nephrology Dialysis Transplantation, doi:10.1093/ndt/gfm151
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Review on uraemic solutes II—Variability in reported concentrations: causes and consequences

Raymond Vanholder1, Nathalie Meert1, Eva Schepers1, Griet Glorieux1, Angel Argiles2, Philippe Brunet3, Gerald Cohen4, Tilman Drüeke5, Harald Mischak6, Goce Spasovski7, Ziad Massy8, Joachim Jankowski9 and for the European Uremic Toxin Work Group (EUTox)

1Nephrology Section, Department of Internal Medicine, University Hospital, Ghent, Belgium,2RD Néphrologie et Néphrologie Dialyse St Guilhem and University Hospital Montpellier,3INSERM 608, Aix Marseille Université, Centre de Néphrologie et Transplantation rénale, Assistance Publique – Hôpitaux de Marseille, France,4Division of Nephrology and Dialysis, Department of Medicine III, Medical University of Vienna, Vienna, Austria,5INSERM Unit 507 and Division of Nephrology, Necker Hospital, Paris, France,6Mosaiques Diagnostics and Therapeutics AG, Hannover, Germany,7Department of Nephrology, University Clinical Center, University of Skopje, Macedonia,8INSERM ERI-12, Amiens, and Amiens University Hospital, UPJV, Amiens, France and9Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin Medizinische Klinik IV, Germany

Correspondence and offprint requests to: Dr Raymond Vanholder, Nephrology Section, 0K12, University Hospital, De Pintelaan 185, B9000. Ghent, Belgium. Email: raymond.vanholder{at}ugent.be



   Abstract
Top
 Abstract
Introduction
 Underlying patterns
 Causes of variability
 Relevance
 Evaluation and interpretation of...
 Conclusions
 Acknowledgements
 References
 
The aim of this manuscript is to initiate a constructive discussion about deviations in measured concentrations of uraemic solutes; these deviations, if not perceived or handled appropriately, may lead to incorrect interpretations of the pathophysiological role of uraemic solutes and/or to erroneous therapeutic decisions. To come to an objective approach towards this problem, variability analysis of reported concentrations may be of help. Striking outliers should either be discarded or considered together with other values which are more consistent with the majority of reported data.

Keywords: uraemia; uraemia toxins; uraemia toxicity; urronic kidney failure



   Introduction
Top
 Abstract
 Introduction
Underlying patterns
 Causes of variability
 Relevance
 Evaluation and interpretation of...
 Conclusions
 Acknowledgements
 References
 
Many compounds retained during kidney failure exert biological/biochemical activity and contribute to the uraemic syndrome, but even if some retention solutes are inert, they may be useful markers of kidney disease or degree of renal dysfunction.

Refined analytical strategies and a better knowledge of biochemistry recently have helped to recognize a growing number of uraemic solutes. In a first review by the European Uremic Toxin Work Group (EUTox), 90 different compounds were tabulated [1]. However, it is very likely that this review revealed only the tip of the iceberg [2,3].

The identification of uraemic retention solutes was accompanied by an increasing number of reports on their concentration. During the preparation of the review on uraemic solutes by EUTox, the scatter of reported concentrations was unexpectedly large for some compounds [1].

In this report, we review the variability in reported concentrations of uraemic solutes and summarize the underlying causes and the importance of taking this variability into account. Subsequently, we will present practical examples for four representative solutes.

All concentrations in this publication are based on CKD stage 4 or 5, corresponding to a glomerular filtration rate (GFR) below 30 ml/min and/or treatment by dialysis.



   Underlying patterns
Top
 Abstract
 Introduction
 Underlying patterns
Causes of variability
 Relevance
 Evaluation and interpretation of...
 Conclusions
 Acknowledgements
 References
 
The chance for concentration scatter increases with the number of reports, especially if different analytical methods have been applied [4]. For some uraemic compounds, however, concentrations are consistent in spite of multiple reports [e.g. atrial natriuretic peptide (ANP)—high vs low: 212.5 ± 163.2 vs 96.2 ± 63.7 ng/l; ratio 2.2] [5,6]. These consistent results were obtained in spite of the application of different test methods. Such consistent concentrations give rise to reliable targets for in vitro testing in cell cultures and as standards for concentrations found in other reports. For many other compounds, however, variability is more pronounced. In addition, consistent results are less valid if they are based on a limited number of analyses and/or analyses performed by few research groups.

If variability is confined to one of a few outliers, exclusion of those outliers as a target is justifiable. Outliers in the upper range deserve most attention, because of their higher toxic/biological activity.

For protein-bound solutes, total concentrations are often reported although toxicity is exerted by the free fraction. In kidney disease, the usual relation between total and free concentration may be disturbed or affected by differences in protein concentration and/or structure.



   Causes of variability
Top
 Abstract
 Introduction
 Underlying patterns
 Causes of variability
Relevance
 Evaluation and interpretation of...
 Conclusions
 Acknowledgements
 References
 
Different degrees of renal dysfunction and/or dialysis strategies
Patients with different levels of renal function may have divergent uraemic solute concentrations. However, even among dialysed patients, the ratios between concentrations may exceed a factor of 100 [7,8], whereas differences between normal vs absent renal function studied by the same method often are smaller, suggesting that differences in concentration rather depend on methodological differences than on renal function per se.

Also differences in dialytic strategies play a role. However, most drastic interventions affecting length and frequency of dialysis, as well as convective clearance, decreased serum ß2-M by no more than 50% [9]. Hence, even major differences in renal function and/or modifications in dialytic approaches have a relatively small impact on solute concentrations, compared with differences among determination methods (see subsequent text).

Differences in solute generation
Differences might also be related to genetic, metabolic, dietary or constitutional factors, all with a potential impact on solute generation, as illustrated by the discrepancies reported by Lesaffer et al. [10] and Fagugli et al. [11] for 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid (CMPF) data. Both determinations were performed in the same laboratory with the same determination technique, in haemodialysis patients treated with comparable dialysis strategies. Nevertheless, measured concentrations differed by a factor of 5.3, which remains a remarkable difference, in view of the essentially nutritional origin of the baseline compound. Of note, the data reported by Lesaffer et al.[10] were obtained in a North-European population, as opposed to those by Fagugli et al. [11] who collected samples in a South-European, Mediterranean population.

The variability in cytokine concentrations [interleukin-1ß(IL-1ß), interleukin-6 (IL-6), interleukin-18 (IL-18) and tumour necrosis factor-{alpha} (TNF-{alpha})] in the context of generation may be related to the microbiological quality of the dialysate, biocompatibility and/or adsorptive capacity of dialysis membranes or inflammatory status [12].

Methodological problems
Much scatter can be attributed to analytical procedures. The higher the number of determination methods, the higher the chance to find variable results [4]. This risk is not confined to separation or analytic methods per se, but may also be linked to the pre-treatment of samples (e.g. derivatization, deproteinization) [13] (see the example which follows for p-cresol and its conjugates).

Methodological overestimation is possible if tests are unspecific [e.g. for certain types of enzyme-linked immunosorbent assays (ELISA)], or if in chromatography peak height is overestimated because several compounds elute simultaneously. True values might be underestimated if extraction or derivatization is inefficient, or if compound is lost (e.g. absorption on chromatographic columns or evaporation).

Errors in concentration units
In one of their publications, Pascual et al. expressed complement factor D in µg/l [14], while in another publication they used mg/l [15], as in all similar reports by other groups [16,17]. Arithmetically, the numbers were similar, only the units differed. The report expressing the data as µg/l very likely used incorrect units [14]. Likewise, Taneda and Monnier reported concentrations for serum pentosidine in the mg/l range [18], whereas all other data have been reported as µg/l [19,20]. This underscores once more the need to compare as many different reports on concentrations as possible.

Structural variants
Finally, compounds may be present in different forms. Publications do not necessarily specify this: for adrenomedullin, either total concentration, or the concentration of the mature and/or the intermediate forms have been reported [21,22]. Only the mature form exerts biological activity [23], although it represents only 10–15% of total concentration [21,22]. Nevertheless, in several publications, the measured form of adrenomedullin is not specified [24,25], making interpretation uncertain.



   Relevance
Top
 Abstract
 Introduction
 Underlying patterns
 Causes of variability
 Relevance
Evaluation and interpretation of...
 Conclusions
 Acknowledgements
 References
 
Problems related to concentration variability are summarized in Table 1.


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  		Table 1. Examples of uraemic compounds and problems related to the variability in their reported concentrations

 
Impact on calculated parameters
Solute determination errors are prone to affect clearance calculations, especially if not only the compound of interest, but also related compound(s), or mere contaminants are included in the non-specific measurement, but as well if no such contamination is present. Those substances are unlikely to display kinetics similar to the compound of interest, resulting in unpredictably divergent clearances, depending also on the time of collection, the subject in whom the sample is collected and the type of sample (e.g. plasma vs dialysate).

A typical example is creatinine: the current determination methods give rise to scatter among each other, due to variable measurement of non-creatinine chromogens [26]. Calculation of GFR by the Modification of Diet in Renal Disease (MDRD) formula or equivalent formulae will result in differing estimations of kidney function [26], depending on the method used for creatinine measurement.

Impact on therapeutic decisions
GFR or serum creatinine values per se are used to guide drug doses and therapeutic decisions, such as the start of dialysis or of secondary prevention. Threshold values for these decisions are mentioned in several guidelines, but mostly without accounting for the variability in creatinine measurements [27], which are generally used to calculate GFR indirectly.

Likewise, serum parathyroid hormone (PTH) concentrations are spread over a broad range, even among CKD stage 5 (end-stage), and even if measured by the same method [28,29]. This divergence can partially be attributed to differences in timing of serum sampling and treatment modalities, but also may depend upon determination methods [30], which not all may take into account the same molecular moieties. The median bias per individual determination method ranges from –44.9 to +123.0% vs the reference, with extremes differing by a factor of 4 [30]. Nevertheless, recent major guidelines proposed precise thresholds for target PTH values, probably insufficiently taking into account inter-assay variation between PTH determination methods [27].

The same risk for inconsistent therapeutic decisions may apply to other marker molecules. Since ß2-microglobulin (ß2-M) concentrations apparently predict outcome of haemodialysis patients [31], it may become a useful marker. Inter-assay variation on ß2-M determination methods has not been checked, but differences among dialysis populations may range by up to a factor of 3 (high value, 55.0 ± 7.9 in patients on low-flux haemodialysis vs low value, 18.4 ± 9.4 mg/l for CAPD-patients—residual GFR 4 ml/min) [32,33]. Although this difference to a large extent might be attributed to differences in dialysis approach, the degree of discrepancy warrants, at least to our opinion, also an evaluation of the variability among determination methods.

Assessment of pathophysiological impact
Asymmetric dimethylarginine (ADMA) concentrations as high as 1.6 ± 1.2 mg/l have been reported [34], but in several studies concentrations range around 0.2 mg/l [35–37], although in each of these studies concentrations were measured in samples collected before the start of routine haemodialysis sessions. ADMA has been linked to cardiovascular disease since it inhibits inducible nitric oxide synthase (iNOS) [38]. An in vivo haemodynamic effect of ADMA was, however, found only at concentrations above 3 mg/l [39]. In another study, a rise of systolic blood pressure was observed in vivo during infusion of ADMA, in the presence of a concentration of 2.0 ± 0.3 mg/l [40]. Therefore, depending on its true concentration, ADMA may or may not be a direct iNOS inhibitor.

Detection of analytical or preparative bias
Finally, divergent results may reveal technical determination errors. Gas chromatographic-mass spectrometric (GC-MS) p-cresol measurements in CKD result in six times higher concentrations [33] than with High Performance Liquid Chromatography (HPLC) [10]. In reality, however, not p-cresol, but its conjugates, p-cresylsulphate and p-cresylglucuronide, are retained in uraemia. Deproteinization, based on acidification [41,42], results in hydrolysis of these conjugates. Since most previously applied determination methods use acid for deproteinization, but the pre-treatment for GC-MS necessitated stronger acidification than that for HPLC, p-cresol was found at higher concentrations with GC-MS. The real retention products, however, are the conjugates. Since this has been recognized only recently, studies on the biological effects of the cresols performed before had focused on p-cresol per se. The question that arose recently was what the biological effect of the conjugates was, as compared with p-cresol itself. Whereas p-cresol inhibits leucocyte function, p-cresylsulphate stimulates baseline leucocyte activity [43]. Hence, finding different p-cresol concentrations with different determination methods, not only led to the detection of an analytical bias, but also to a new toxicity pattern opposite to previous assumptions.



   Evaluation and interpretation of variability
Top
 Abstract
 Introduction
 Underlying patterns
 Causes of variability
 Relevance
 Evaluation and interpretation of...
Conclusions
 Acknowledgements
 References
 
Implications
Preconceived protocols describing an exact approach that helps to decide whether a given concentration fits with those of other studies are lacking.

The main strategy depending upon this procedure is the selection of concentrations for in vitro studies. A previous report proposed that the first evaluation should be of the highest measured concentration, because this represents the extreme which patients experience [1]. However, this high concentration may lead to an overestimation of toxicity if the threshold value is an upward outlier. Therefore, analysis of the variability of reported concentrations is a valuable approach, allowing the exclusion of outliers in favour of other, more realistic, concentrations.

Strategies to assess reported variability
Concentrations from a sufficient number of studies should be available for comparison. Ideally, these should emanate from different research groups and be based on different determination methods. It is useful, to include in the survey, a minimum number of values generated per individual research group. While selecting, values obtained from a large number of samples should be preferred.

However, it is extremely difficult to find a large number of reports for most compounds. Proposing a target number is arbitrary. In a recent comparative survey, this number was set at eight references [4]. For many compounds, however, this figure cannot be attained.

A critical assessment of reported concentrations should include a variability analysis, to be taken into account in the interpretation of the data.

We propose two different approaches. The first one is to define outliers by scatter plot analysis (box and whisker plot). A value is separated out as an outlier if the distance to the closest outline of the box is ≥1.5 times larger than the height of the box (interquartile range). Examples for four different molecules [homocysteine [44–51]; hippuric acid [10,11,52–57]; IL-6 [8,12,29,58–62]; and vasoactive intestinal peptide (VIP) [63–70]] are shown in Figure 1, with the raw data on which this approach is based in Table 2. In this table, outliers identified by box and whisker approach are indicated by an underscore. Alternatively, we propose to define outliers by calculating the ratio between the concentration under consideration (C) and the lowest (L) extreme concentration (C/L). The definition of the threshold in that case is arbitrary, but we propose a C/L >10. In Table 2, outliers according to this approach are indicated in italics. A C/L >10 is consistent with a substantial variability.


Figure 1
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  		Fig. 1. Graphic illustration of results of box and whisker analysis for homocysteine (A), hippuric acid (B), interleukin-6 (C) and vasoactive intestinal active peptide (D) (detailed values reported in Table 2). The insert in panel A shows the same analysis for homocysteine, if the highest reported value is set at 8.2 instead of 8.1 mg/l (the latter is the actual reported highest value). Outliers are found for hippuric acid (B), vasointestinal active peptide (D) and homocysteine, if the highest value is set at 8.2 mg/l.

 

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  		Table 2. Comparison of values obtained for four representative uraemic solutes

 
Obviously, it is not always clear whether differences in concentration are attributable to either differences in methodology or in generation. It is unlikely, however, that up to 30-fold differences in solute generation in relatively homogeneous haemodialysis populations, as seen for e.g. IL-6, would be solely attributable to differences in generation.

Especially high range outliers should be considered with caution, whatever their origin. In the presence of such an outlier(s), it is advisable to take the second highest or even the third highest value into account as well.



   Conclusions
Top
 Abstract
 Introduction
 Underlying patterns
 Causes of variability
 Relevance
 Evaluation and interpretation of...
 Conclusions
Acknowledgements
 References
 
Uraemic solute concentrations reported in the literature are frequently subject to scatter, owing to the influence of various factors, above all to inaccuracies in methodological approaches. Deviations in measured concentrations may lead to incorrect interpretations of the pathophysiological role of uraemic solutes and/or to erroneous therapeutic decisions. When choosing solute concentrations for in vitro tests or when comparing newly determined concentrations with those reported previously, potential discrepancies among available values should be carefully analysed and taken into account. To come to an objective approach to this problem, variability analysis of reported concentrations may be of help. Striking outliers either should be discarded or analysed together with other values when more consistent with the majority of reported data.



   Acknowledgements
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 Abstract
 Introduction
 Underlying patterns
 Causes of variability
 Relevance
 Evaluation and interpretation of...
 Conclusions
 Acknowledgements
References
 
The European Uremic Toxin Work Group (EUTox) has been created within the European Society for Artificial Organs (ESAO) to discuss and analyse matters related to the identification, characterization, analytic determination, and evaluation of biological activity of uraemic retention solutes. More information about EUTox which is responsible for this publication, can be obtained at the website: http://uremic-toxins.org. E-mail: raymond.vanholder{at}ugent.be.

The current members of EUTox are: A., Montpellier, France; U. Baurmeister, Berlin, Germany; J. Beige, Leipzig, Germany; P. Brouckaert, Ghent, Belgium; P., Marseille, France; J. Chudek, Katowice, Poland; G.C., Vienna, Austria; P.P. De Deyn, Antwerp, Belgium; T.D., Paris, France; G.G., Ghent, Belgium; S Herget-Rosenthal, Essen, Germany; W Hörl, Vienna, Austria; J.J., Berlin, Germany; A Jörres, Berlin, Germany; Z.M., Amiens, France; H.M., Hannover, Germany; A. Perna, Naples, Italy; M. Rodriguez, Cordoba, Spain; G.S., Skopje, Macedonia; B. Stegmayr, Umea; P. Stenvinkel, Stockholm, Sweden; P. Thornalley, Essex, UK; R.V., Ghent, Belgium; C. Wanner, Würzburg, Germany; A. Wiecek, Katowice, Poland and W. Zidek, Berlin, Germany. Members who authored this publication are indicated by their initails.

The activities of the EUTox group are supported by the following industries: Amgen, Baxter Healthcare Corporation, Fresenius Medical Care, Gambro, Genzyme, Hoffmann-La Roche and Membrana GMBH.

Conflict of interest statement. None declared.



   References
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 Abstract
 Introduction
 Underlying patterns
 Causes of variability
 Relevance
 Evaluation and interpretation of...
 Conclusions
 Acknowledgements
 References
 

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Received for publication: 12.12.06
Accepted in revised form: 27. 2.07


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