Are the classical markers sufficient to describe uremic solute
accumulation in dialyzed patients? Hippurates reconsidered
Citation for published version (APA):
Schoots, A. C., Dijkstra, J. B., Ringoir, S. M. G., Vanholder, R., & Cramers, C. A. M. G. (1988). Are the classical
markers sufficient to describe uremic solute accumulation in dialyzed patients? Hippurates reconsidered. Clinical
Chemistry, 34(6), 1022-1029.
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Published: 01/01/1988
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CLIN. CHEM. 34/6, 1022-1029 (1988)
Are the Classical Markers Sufficientto DesCnbeUremic Solute Accumulationin Dialyzed
Patients? Hippurates Reconsidered
A. C. Schoots,1 J. B. Dljkstra,2 S. M. G. Rlngolr,3R. Vanholder,3 and C. A. Cramers1
Interdependencies of accumulated solutes, analyzed by liq-uid chromatography in dialyzed and non-dialyzed patients, were studied by multivariate statistical analysis. In principal component analysis, three principal components (PC1-PC3) were retained from the data on 22 accumulated compounds in dialyzed patients, whereas only one principal component was retained from analogous data of a non-dialyzed patient group. PCi in the dialyzed patient group comprises concen-trations of hippuric acid, p-hydroxyhippuric acid, tryptophan,
and five unidentified fluorescent solutes in serum.
Concen-trations of the classical markers urea, uric acid, creatinine, and phosphate were closely related to PC2 in these patients. Indoleacetic acid and two unidentified fluorescent com-pounds constitute PC3. The comcom-pounds associated with the groups found by principal component analysis may be char-acterized by chemical structure and by the mechanism of their excretion via the remaining nephrons of dialyzed pa-tients. In the non-dialyzed group, most of the solutes could be described by a single PC. This PC and PCi from the dialyzed group correlated significantly with residual renal function, and with total ultraviolet absorbance and total fluorescence emis-sion. The data suggest that it is of value to introduce a marker of uremic solute retention in addition to urea, to account for renal-function-related organic-acid-like” compounds that are excreted by renal tubular secretion in dialyzed patients. The hippurates may serve this purpose.
Addftlonal Keyphrases: uremia dialysis principal-compo-nent analysis middle molecules” chromatography,liquid
multivariate analysis tubular secretion
The debate as to the identity of the toxins responsible for
the uremic syndrome began more than a century ago. Bright observed in 1931 that, although urea was found to be
accumulated in patients with renal failure, its concentration was not a good measure of the severity of symptoms. Since
then, many solutes accumulating in the body fluids of
uremic patients have been isolated and identified, parallel
to the development of analytical (bio)chemistry.
The long list of candidate toxins includes solutes with a wide range of molecular mass, chemical structure, and
biochemical function (1-4): urea, creatinine, phenols, in-doles, guanidino-, pyrimidine-, and purine-compounds, or-ganic acids, polyols, salts, trace elements, hypothetical
“middle molecules,” parathyrin, peptide hormones, and
low-molecular-mass proteins such as f32-microglobulin. They
may occur in free form, or show protein binding, and (on)are conjugated to sulfate or glucuronide.
‘Laboratory for Instrumental Analysis, Faculty of Chemical
Engineering, Eindhoven University of Technology,P.O. Box 513,
5600 MB, Eindhoven, The Netherlands.
2Computing Centre and Department of Statistics, Faculty of
Mathematics, EindhovenUniversity ofTechnology.
3Department of Nephrology, University Hospital, Ghent, Bel-gium.
Received November 5,1987; acceptedFebruary 10, 1988.
None of the proposed toxins or solute class of toxins has
conclusively been shown to be responsible for the wide range
of uremic symptoms. Nevertheless, chronic dialysis therapy
has been successful in the treatment of end-stage renal
patients, because it reverses several symptoms, at least
partly. Therefore the question of objective criteria for ade-quate dialysis is still topical.
Although there is some consensus about basic criteria for
adequate dialysis (5-8), such as maintaining fluid and
electrolyte balance, adequacy is difficult todefine aslong as there is no information about the identity of the solutes that should be removed preferentially. Moreover, dialysis tuned to the needs of individual patients requires knowledge of both the identity of the “toxins” and the structure of the
dialyzed patients’ population relative to these toxins. Some time ago, we suggested a proffling approach with use of modern analytical techniques and multivariate anal-ysis to study accumulation of uremic solutes (9,10).
Twenty-two characteristic uremic solutes in sera of dialyzed and
non-dialyzed uremic patients were subjected to principal
component analysis, in order to explore interdependencies
between these concentrations and their distribution in
dif-ferent patients. These ultraviolet-absorbing and (or)
fluores-cent solutes were analyzed by gradient-elution
high-per-formance liquid chromatography (HPLC) as described
previ-ously (10, 11).
Although multivariate techniques have been used by Lowrie et al. (7), to our knowledge this is the first time that
a multivariate study in the present form has been reported. Materials and Methods
Patients and Sera
Pre-dialysis blood samples were collected from 33 uremic dialyzed patients and from 32 non-dialyzed patients.
Dia-lyzed patients were treated by single-needle hemodialysis,
with use ofdifferent types of dialyzers. Serum samples were
ultrafiltered with “Centrifree” ultrafiltration units (Amicon,
Danvers, MA) to remove serum proteins. The ifitrate was
diluted with an equal volume of a solution of internal
standard, naphthalene sulfonic acid (37 mg/L), and subse-quently analyzed by HPLC.
Procedures
HPLC. This was performed as described previously (10, 11). A column of “Ultrasphere Octyl” (C8-modifled silica), 4.6 mm (i.d.) x 25 cm, with 5-pm particles, was used in
conjunction with an Ultrasphere Octyl guard column, 2 mm
(i.d.) x 3 cm, with 10-p.m particles.
The solvent gradient was linear from 100% aqueous
ammomum formate buffer (50 mmol/L, pH 4) to 60%
metha-nolJ4O% buffer within 45 miii. The flow rate was 1 mL/min.
The separation column and the solvent were kept at 25#{176}C by means of athermostated bath and column water jacket.
The chromatograph consisted of a Model 421 controller, two Model 100A double-piston pumps, a Model 160
CLINICALCHEMISTRY, Vol. 34, No. 6, 1988 1023 0.05 A full scale) and a Model 500 autosanipler (all from
Beckman Instruments, Fullerton, CA). Additionally, we
used fluorescence detection at 280 n.m (excitation) and 340 nm (emission), in a Model RF530 double-monochromator
fluorescence detector (Shimadzu, Tokyo, Japan).
Data acquisition and statistics. For chromatographic data acquisition and handling we used a Model 761S data interface and Model 2600 chromatography software (both
from Nelson Analytical, Cupertino, CA). Data were read in
SAS data ifies and analyzed with SAS statistical software
(SAS Institute Inc., Cary, NC). We used the SAS-procedures
FACTORand cona for principal component analysis and
correlation analysis, respectively (12). Total ultraviolet
ab-sorbance at 254 n.m and total fluorescence emission (at 280
n.m excitation and 340 n.m emission) were evaluated by
determining total peak areas under the ultraviolet and
fluorescence traces of the HPLC chromatograms.
Principal component analysis. In principal component (PC) analysis a set of measured variables may be trans-formed into a smaller set of non-correlated variates that
describe a large proportion of the variation in the original
variable set. In this way a dimension reduction of the
original data is obtained.
The variates or principal components are linear
combina-tions of the measured variables, according to: PC, = W#{149}a
where W are variable weighting coefficients andx3are the
measured variable scores (j = 1,2,. ..p;p variables, and i=
1,2,. . .k; k components, where k p).
The PCs are extracted so that PCi is the linear combina-tion describing the largest amount of variacombina-tion in the data,
and PC2, PC3, etc. comprise linear combinations that
de-scribe subsequent largest amounts of variation in such a
way that PCi, PC2, etc. are all non-correlated.
This is done by calculating the subsequent eigenvalues A
and corresponding eigenvectors y of the correlation matrix
R. The eigenvectors are the respective weighting coefficient
vectors (W) as encountered in the equation given above.
Principal components are extracted under the constraints of = 0 and yj1’ = 1, where y, and y2 denote subsequent
eigenvectors.
The maximum number of extracted components is equal to the number of variables. Total variance of the
standard-ized data is the sum of the diagonal elements of the
correlation matrix, which amounts to p, the number of variables.
The variance explained by individual principal
compo-nents equals the corresponding eigenvalue divided by the
total variance: X11p.There are several criteria for the
num-ber of components toretain. In the present study, we used a
discontinuity in a plot of principal component eigenvalues
as a function of extraction order. By using a correlation
matrix rather than a variance-covariance matrix, data
were standardized to account for large differences in
vari-ance ofvariables expressed in different scales and units.
After extraction of PCs, orthogonal rotation of the PC
pattern was performed with the varimax method. This
consists of a maximization of the variance in the columns of
the PC matrix, which results in values for the column
elements as near as possible to 0, -1, or 1.
We used the FACTOR procedure from SAS statistical
soft-ware (12).
Results
Figure 1 shows representative chromatograms of
ultrafil-tered sera. These proffles will be discussed below. Besides
the 20 compounds measured with HPLC, phosphate and urea were quantified conventionally.
A correlation matrix of the solute concentrations was
factored in a principal component analysis, to obtain a
smaller number of mutually independent “summary
varia-bles,” and to allow us to visualize correlations and
interde-pendencies between the concentrations of the respective
solutes.
Dialyzed uremic patients. After judgment of a plot (Figure 2a) of eigenvalues vs PC extraction number, three principal
components were retained from the data of the
hemodia-lyzed group. These three components describe 49% of total variance in the scaled data (PC 1, 22%; PC2, 15%; PC3, 12%).
After orthogonal rotation (varimax), a factor pattern was
obtained, of which a projection on the PC1-PC2 plane is
shown in Figure 3.
Table i lists variables and their loadings on the principal components. Four “clusters” of solutes may be distinguished in Figure 3 and Table 1.
Group A has high loadings on exclusively PCi. Group B is closely related to PC2, group C has very high loadings on
PC3, and group D seems to be related to PC2 and less so to PCi.
Here it may be noted that PC2 summarizes a number of
solutes that hitherto have been used as clinical markers of
uremia: urea, uric acid, creatinine, and phosphate.
On the other hand, PCi comprises a number of aromatic
and indolic compounds, such as p-hydroxyhippuric acid,
hippuric acid, tryptophan, and the unidentified fluorescent solutes UKF1, UKF4, and UKF7A; and it correlates signifi-cantly with residual renal ftmction in these dialyzed pa-tients. Furthermore, PCi correlates significantly with the
more-general measures of accumulation, total ultraviolet absorbance and total fluorescence emission, that are de-scribed in the Methods section. Table 2 gives a correlation matrix for the PCi, PC2, and PC3 scores, residual renal function, total ultraviolet absorbance, and total fluores-cence.
Non-dialyzed patients. From the plot of eigenvalues in
Figure 2b, we decided that only one PC should be retained
after factoring the correlation matrix of the data of
non-dialyzed (preterminal) uremic patients. This single principal component describes 49% of the variance in the scaled data.
Loadings of the original solute concentrations on this PC are
given in Table 3. The PC scores correlate significantly with residual renal function, total ultraviolet absorbance, and
total fluorescence emission, as was also observed for PCi in
the group of dialyzed patients. Table 4 gives a correlation
matrix.
Structure of the dialyzed-patients group. From the original
data and the weights of the variables on the principal
components, we calculated standardized patient scores on
the“summary variables” PCi, PC2, and PC3.
The data for PCi and PC2 are given in the bivariate scatter plot in Figure 4.
Figure 1 shows HPLC chromatograms (urea and
phos-phate concentrations are given in the legend) for sera of patients with “extreme” PCi and PC2 scores. Patient 1
shows high concentrations of solutes 6, 7, a, and d (p-hydroxyhippuric acid, hippuric acid, UKF1, and UKF4,
respectively) associated with PCi. Only intermediate con-centrations of solutes associated with PC2-e.g., peaks1,3,
h(flff
d C f I 13 4 7 Ii I 1.2 HJiH
IL
7 U Ir -j U. C PAT. 32 m 0 -0- 40 t 5 > 34
PAT. 18 3 4 6 12ui
8 t mm. 40 40 0 0 - t mm. 40 j U. 0 PAT. 15 2 3 ‘-4 b hxr
5L1LLiL
-0-- t mn nflFig. 1. HPLCchromatograms(ultraviolettrace below,fluorescencetrace on top) of ultrafilteredsera of tour patIents(1,15,32, and 16) forwhomPC scores are shown In FIgure4
Correspondingureaconoenlratlore:272,38.5,23.9, and 27.9 mmoVLCorrespondingphosphateconcentratIons:1.75,1.93,1.87, and 1.36 mmoUL,respectively.Peak
Identification,ultraviolettrace:1,crealinlne;2,peeudoufldlne;3,urIcacid;h, hypacanlt*ie;4, UK4;5, tiCS; 6; p.hydimyhlppurlc acId; 7.hlppuricacId;8, Internal
alandwd. Fluc,acence trace: UKFI; b.t,oelne; UKF3;d,UKF4;e,UKF5;f,kidacyleulfate;g,trtephan;h, UKF6;1.UKF7A;J,UKF7;k UKF8;j, ultravioletInternal
aSandard(hashIghfluorescenceem&sslon);m,3-Indoleaceticacid
and ha (creatinine, uric acid, and hypoxanthine,
respective-ly), but also urea and phosphate (see figure legends)-appear in this patient. Patient 15, with a high score for PC2,
has an intermediate score for PCi. Patient 32 has low scores
for both PCi and PC2, and patient 16 combines low scores for PC2 with an intermediate value for PCi.
We saw no instance of a high score for one PC and a low score for the other.
Accumulation as a function of residual creatinine clear-ance. Concentrations of the 22 compounds in the combined
dialyzed and non-dialyzed patient groups were plotted vs
residual creatinine clearance. Mainly two types of curves
were obtained, one in which there was a significant
concen-tration increase when residual creatinine clearance was 60
mllmin, and one in which this occurred at only 20 mL/min
(see also Table 5). The first type was found for urea, uric
acid, creatinine, pseudouridine, UK5, and UKF3, all
(main-ly) belonging to PC2. The second type was observed with
p-hydroxyhippuric acid, hippuric acid, UKF1, UKF4, and
UKF7A, belonging to PCi; phosphate (PC2); and UKF7,
UKF8, and 3-indoleacetic acid from PC3. Figure 5a shows
Ae
1
4
0
0 5.
FIg. 2. Plots of eigenvalues, as a function ofextraction orderofpnncupalcomponentsfroma correlationmatrixof22urernlc solutes: (left) for agroup of dialyzed patients (HD);(right) for agroup of non-dialyzed(preterminal)patients (PT)
PCI hipp. ‘I / ukf A’ ukf phIipr tyr S ID
Group Variable PCi PC2 PC3 HPLC peak cod.0
A Hippurate 0.77 - 7 rp Tryptophan IJKF4 0.76 0.72 -g d #{149} ukf UKF5 UKF1 0.72 0.62 -e a #{149}ukf7A / cis ic;N . #{149}‘ B UKF7A p.OH-Hippurate Uric acid 0.62 0.43 -0.79 -I 6 3 #{149}uk4
\
ucf3 #{149} O- ‘- \ .._-p8, C D Urea Hypoxanthlne Phosphate UKF6 UKF7 UKF8 3-Indoleacetate Pseudourldlne Creatlnlne UK5 UKF3 Indoxylsulfate -0.24 0.28 0.45 0.37 0.46 0.73 0.64 0.59 0.55 -0.68 0.63 0.47 0.56 0.42 -0.91 0.91 0.91 -Coflv.d hx Cony. h j k m 2 1 5 c f .lE 0 . / tkf 3-IUU Zg-/ ‘\ . 0.5”. . P uIea ‘&kf 6 ‘S ur’,c -PC 2FIg.3. Principalcomponentpaftem, showingloadings of 22 uremlc
solutes onPCi and PC2
Soltiteedeecrbed by PC3 are localizedaroundthe origInInthIsrepresentation.
t hippurlcacid; e tryptophan;p.hh, p4roxyhIppurIc acid; tyroelne;
3-Isa 3.indoleaoetlcacid; incj Indoxyleulfate;crea,creatinine;pa pseudouridine; l hypoxenthlne;P, phosphate;uric,uric acid
loadingsrepresentthe correlationcoefficientfor each variableand the
respectiveprincipal components.
0ForHPLC peak codes,refer toFIgure1.
CDes representabsolutevaluesofloadings smaller than0.20; loadIngs
of UK4 (HPLC peak4InFIgure 1) on all three PCswere<0.25.
dConv. means “measured conventionally.”
5
.1 12
CLINICALCHEMISTRY, Vol. 34, No. 6, 1988 1025 4 2 1 .2 HO .3
4
S S .. . . S #{149}#{149}#{149} 0 4 B 12 16 20 .--- numberThe region between residual creatinine clearance = 5 roll
mm and 0 mlimin (i.e., the dialyzed patients) is expanded in
Figure 5b.
Discussion
In the present andy we have examined the
interdependen-des of the concentrations of 22 solutes in uremic sera. They
include urea, phosphate, creatinine, pseudouridine, uric
acid, hypoxanthine, p-hydroxyhippuric acid, hippuric acid,
tyrosine, indoxylsulfate, tryptophan, and 3-indoleacetic
acid, and some unknown ultraviolet-absorbing and
fluores-cent compounds. The unknown compounds encountered in
the HPLC chromatograms could be quantified from the peak height. The solutes originate from different metabolic
4 2 .1 ... PT 0 4 8 12 16 20 -*- number
processes. Urea is an end product of protein catabolism.
Phosphate is related to protein intake or, more generally, to
diet (possibly as phospholipids) and as such is correlated
with urea. Pseudouridine is a product of specific
tRNA-turnover. Uric acid and hypoxanthine are more-general
products of nucleic acid metabolism. Creatinine is the
product of phosphocreatine degradation. Hippuric acid
mainly originates from the diet, being formed after
conjuga-tion of glycine to benzoic acid; the latter is widely used as a
food preservative, occurs naturally in different foodstuffs,
and is a product ofphenylalanine metabolism.
p-Hydroxy-hippuric acid may be an endogenous compound related to
tyrosine metabolism.
Table t. Loadings aof Solute Concentrations
on
ThreePrincipal Components (PC), for Sara of Dialyzed
waste products urea, uric acid, and creatinine. Both urea
and phosphate concentrations do correlate with daily
pro-tein intake and were found to be correlated significantly
with each other in the present study (r = 0.46, P 0.002). It is interesting to observe that they are located near to each other in the PC pattern of Figure 3 and that they are closely
linkedto PC2. Uric add and its precursor hypoxanthine are
products of nucleic acid metabolism, and both have high
loadings on PC2 and not on PCi. Urea has been used as a
marker in the approach of “urea kinetic modelling” to
account for toxicity arising from protein breakdown
prod-ucts (20, 21). Phosphate retention causes high
concentra-tions of parathyrin, which has been shown to exert various toxic effects (22,23).
The solutes correlating highly with PC3 are
3-indoleace-tic acid and two unknown fluorescent solutes. There is no
significant correlation between PC3 scores on one side and
residual renal function, total ultraviolet absorbance, or total
fluorescence emission on the other (Table 2).
Important attributes of the compounds that appear to
determine the association with different principal compo-nents are both chemical structure and the (cor)relation of the solute concentrations with residual renal function. Ta-ble 4 gives some properties of the analyzed solutes.
The correlation between concentrations in serum and
Tot.FL RCC0 residual renal function may to some extent beexplained by
-0.57 different clearances of the solutes by the dialyzer. In vitro
P <0.0006 dialyzer clearances relative to urea (recalculated for any
n.s. protein binding and protein volume exclusion) tend to be
n.s. lower for the solutes associated with PCi and PC3, as
compared with PC2 compounds (Table 5) (24).
n.s Yet there is another attribute of thecompounds that could
explain the observed division of solute groups. It concerns
the mechanism of excretion by the remRining nephrons.
This may be glomerular filtration or a combination of
filtration and tubular secretion. Porter et al. (19) showed
that organic acids do not significantly increase in serum
until the residual creatinine clearance has declined to 20 znLfinin. In the present study this was observed for hippuric
PCi PC2 PC3 Tot. UV PCi 1 0 0 0.67 P <0.0001 PC2 1 0 Pc3 1 Tot.UV 1 Tot. FL. 0.43 P<0.02 n.s. n.s. 0.54 P<0.001 Salute UKF3 UKF1 Pseudouridine Urea Hippurate lndoxylsulfate UKF6 UKF8 UKF5 p-OH-Hlppurate Phosphate 3-Indoleacetate UKF7A PCI 0.97 0.97 0.97 0.90 0.89 0.87 0.86 0.82 0.79 0.78 0.73 0.66 0.53 4 PC I
43
2 1 0 -I -2 S 3 4 S #{149}6 10 ______I______ -#{149} 20 5 17 19 S#{149}2 16 26 27 #{149} Sr ‘30 ‘32 Tot.UV Tot. FL 1 0.59 P<0.007 RcC0 0.53 P<0.02 7. .9 Se 15 S 12 1 #{149} 14 ,24 #{149} 28 S #{149}28 31 -2 -1 0 1 2 - PC2 3FIg. 4. Blvailatescatterplotof PCi and PC2 scores for 32dialyzed uremic patients
The first principal component (“summary variable”) for the group of dialyzed patients appears to be formed by
aromatic and indoliccompounds, most of which show
signifi-cant individual correlation with residual renal function
(Table 5). This has been reported earlier for the
ultraviolet-absorbing compounds (13). A number of them exhibit
pro-tein binding (Table 5) (11).
Aromatic compounds exert various toxic effects, especially
inhibition of cerebral enzyme action (14) and inhibit ion transport across cell membranes in various tissues (15-19). Although some of the fluorescent PCi solutes are not yet
identified, they may also be indolic or aromatic compounds,
as judged from their fluorescence emission at the wave-length combination we used.
The second PC seems to be related to a number of compounds whose concentrations are notdirectly correlated
with residual renal function in terms ofresidual creatinine
clearance, and that have been used as uremic markers in the past, among which are phosphate and the nitrogenous
Table 2. Correlation5 Matrix of PC-Scores, Total Ultraviolet Abeorbance, Total Fluorescence Emission,
and Residual Renal Function for a Group of 33 Dialyzed Uremic Patients
‘p correlation.0RCC, resIdualrenalcreatinlne clearance.#{176}n.s.:not
significant (P>0.05).
Table 3. Loadlngs ofSolute Concentrations on PCI In the Non-Dialyzed Patient Group
‘Loadings represent correlation coefficientsof the variables with PCi.
Table 4. Correlatlon Matrix of PrIncipal Component
Score, Total UltravIolet Absorbance, Total
Fluorescence Emission, and Residual Renal Function
for 32 Non-DIalyzed Uremic Patients
PCI Tot. UV Tot.FL
-0.81 P<0.0001
-0.65
P<0.002
n.s
‘Pearson correlation.0RCC,residual renal creatinine clearance. not significant (P >0.05).
Ss.,a 1051 5051100uIl Q51t101nS Ss,un C,51tft,tn. Os95519.81 Cl51t1n190 $u.s p-G4-*ltpp.scld 5. 95,19.81 5Ut.
CIIuIcs. OtaIyzsd 0 P85-01.19.9 Pets. IX 100) Cl.wSOcs. 0101950 85-dIalyzed Pets. (0 1000) C1,w.scs. Dialyzed 0 8s-dtslyl.d Puts.
I I I I I I I I I 1e( I I I I I I I 1 I I I I I I 000j - lZr .
I
I50f_ .... . .... .. .. 9 ,. - . . ‘ ‘: ‘:: ,“
::
‘‘ , . . 01 I I I I ) I I I 9 II I o PiI .I1IIII&OIIi I#{149}#{149}0jpJ.1.1, I 0 30 00 90 120 100 0 30 50 90 120 150 0 30 00 00 120 110 8.C 18Jul51 C 1.1./sir.) 90C 8./nt.,)Plot ot Dana os. V. 951199.1 CI.SSI. Dana C,s.1101n, so 950190.1 OlItInInl p-Gl-Hlp,.olc acid os 005105.1 C.s.t.
Cl.arancd. 0151950 PltIsstS. III 100) Clsar..ce. 01a19.0 PetiustS. IX 1000) CleI..nc.. 01.1,0.9 PetIests.
II1III ii I1II1IIII1 II1)1I1II1III11II1)1 III#{149}
IL
I I II 11111111)! III)230L - -
.
L
. , . . .,,, : . I I .5 -#{149}I . .5 5. - F 200 -5 9 - 9, . 0 . :‘ . .F
. ,. 170 1 9 0 I:
110 .4 I - - . ‘ e I I . . . . I #{149} us 3 :. I I I I I I I I I I I I I I I i ‘I 0 I I I I I lI I I I I I I I I I 15I 90C 18./.InI .01.110FIg.5. (a, upper panels)Plots ofserum concentrationsof urea,creatinine,and phydroxyhlppurlc acid as a functionof residualcreatinineclearance
Dataforbothnondalyzed(resIdualcreatinlneclearance,>5 mLJmln)anddialyzed(residualcreatinlneclearance.<5mLln) we shown
(b, biterpanels) Plots similar to those of a,but for dialyzed patients only
acid, p-hydroxyhippuric acid, UKF1, UKF4, and IJKF7A, edly, hippurate). As the concentrations of the latter solutes
all belonging toPCi. These substances probably are mostly in the serum of dialyzed patients werereported (11) to be
excreted by renal tubular secretion and follow the “organic significantly smaller (p-hydroxyhippuric acid range 4-63
acid secretory meotheniem” (25). On the otherhand, concen- pznol/L, hippuric acid range 36-894 zmol/L, both for the
trations in serum of anumber ofcompounds associated with non-protein-bound fraction) than this limit, they will still be
PC2 hadincreased significantly atresidual creatinine clear- excreted mainly by tubular secretion in intact nephrons of ances of 60 3JJmin: urea,creatinine, pseudouridine, UK5, theresidual renal mass in dialyzed uremic patients.
anduric acid. This suggestsexcretion, atleast predominant- In different studies the inhibitory effect ofuremic serum
ly, byfiltration. In normal functioning nephrons, the contri- on p-aminohippurate and o-iodohippurate transport in iso-bution oftubular secretiontototal excretion of p-aminohip- lated tubules and kidney slices has been reported (16,17,
purate is more than sixfold that ofglomerular filtration, as 27). Inhibition ofion transport across cell membranes in
long asthe concentration in serum is <1000-1500 imol/L. other tissues has alsobeen reported (15,18). It wasproposed
Above this value the secretory mechanismbecomes saturat- that the inhibition of tubular flmction was exerted by high
ed (25). It has been shown by Smith et al. (26) that p- concentrations of hippurates and indoleacetic acids, and not
hydroxyhippuric acid and p-aminohippurate have identical by urea, uric acid, and creatinine (16). Unlike the organic
renal clearances inhumane. Thereforetheabove-mentioned acids, these latter solutes are associated with the second
limit of 1000-1500 pmol/L for p-aminohippurate will con- principal component (PC2) in the present study.
ceivably be valid also for p-hydroxyhippurate (and, suppos- There is evidence for the “toxicity” of solutes from both
Compound PC. rRCCb(P) PBL(%)5 Kb/Kb,urea10 Typ. ofRCC-concn curve Hippurlc acid p-OH-Hlppuncacid Tryptophan UKF4 UKF5 UKF1 UKF7A 1 1 1 1 1 1 1 -0.60 (0.0001) -0.57 (0.0001) + -‘ -0.37(0.02) -0.30(0.04) -0.36(0.02) 38 15 61 0 0 25 12 0.48 0.57 0.24 0.42 0.25 0.43 0.64 A A -A -A A Urlcacld Urea Hypoxanthine Phosphate UKF6 2 2 2 2 2 3g 0 n.a!I 25’ 74 0.86 1 n.a. n.a. 0.26 B B -A A UKF7 UKF8 3-Indole-acetate 3 3 3 55 9 71 0.33 0.53 0.24 A A A Pseudouridine Creatinine UK5 UKF3 2(+1)’ 2(#{247}1) 2(+1) 2(+1) 0 0 11 0 0.67 0.87 0.75 0.47 B B B B Indoxylsulfate 1(+2) 90 0.10 A
‘PrincIpal component associated withthecompound.
5rRCC,correlation to residualcreatinineclearance.Spearmanrankcorrelation.
0PBLproteinbinding level(%) (11).
10Kb/Kb,urea,dialyzerclearanceofthesoluterelativeto ureaon 0.9 m2cuprophanmembranein vItro (24), recalculatedfor proteinbinding,if any.
RCC-(soluteconcentration)curves: A, bendat20 mUmin;B, bendat 60 mL/min.
+ positivecorrelation;-not significant(P>0.05).
0FromFarrelletal.(32).
“n.a.:notavailable.
‘Phosphate protein binding, from Walser(3. ‘PCnumberwithhighestcorrelationfirst.
Table 5. Some PropertIes of the Uremlc Solutes under Study
PCi and PC2-urea and phosphate representing protein
toxicity, bone disease, and parathyrin toxicity, respectively,
and the organic acids as inhibitors of ion transport in tissues
and of cerebral enzymes (14). Therefore, dialysis should be designed to remove compounds from both groups, and it is
important to know what are the relative PC scores
(“sum-mary concentrations”) for the groups of solutes in the
individual dialyzed patients.
The structure of the patient group with respect to the
uncorrelated principal components is shown in Figure 4. An
adequate amount of dialysis in one patient that brings down
the level of 0PC2” to within acceptable limits may not suffice
to attain acceptable levels of “PCi,” because the relative
scores on the components may be very different among
patients (e.g., patients i and i5 in Figure 4).As an example
we consider patient 1. When this patient is dialyzed for urea
(associated to PC2) according to patient kinetic modelling
results, a small amount of dialysis may be enough, because
the score for PC2 is only of intermediate magnitude.
Howev-er, this may not suffice to decrease the concentrations in
serum of solutes associated to PCi, which are relatively
high in this patient’s serum, to acceptable values.
PC analysis on the data of the non-dialyzed patient group
appears to result in one single component (PCi). This single
PC contains almost all those compounds that are associated
with three independent principal components in the data for
the dialyzed patients. Compounds such as
p-hydroxyhip-puric acid and hippuric acid, described by PCi in the
dialyzed group, only appeared in the blood of non-dialyzed
patients when residual renal function decreased below 20
mL/min. This accords with reported data (19) and may be
part of the answer to the question of why additional
princi-pal components appear in dioiyzed patients (residual renal function of 0 to 5 mLfmin).
Different groups of uremia-accumulated compounds with
which the concentrations in serum were associated could be
distinguished in the dialyzed patients’ sera. Choosing a
single marker, such as urea, to describe uremic solute
retention seems only justified in the case of non-dialyzed
patients whose residual renal function exceeds 20 mllmin.
In this group the concentrations of almost all accumulated
solutes are inter-correlated and also with residual renal
function.
In the group of dialyzed patients, relative scores forthe
“summary concentrations” differ between patients.
Sargent (20), who advocates the otherwise rational
ap-proach of urea kinetic modelling, stated that”. . .the goal of
modelling therapy should not be overly ambitious in its
attempt to create an all-indusive description of uremia.”
The present study shows that concentrations of a group of
“organic acid-like” substances vary relatively independent
from those of another group, including classical markers
such as urea, creatinine, and uric acid, and that the relative
“concentrations” of these groups differ between patients.
Dialyzed patients with negligible residual creatinine
clear-ance generally have a higher ratio of PCi to PC2 than do
patients with some remaining renal function or, to put it
loosely, have relatively high concentrations of “organic acid”
as compared with urea and creatinine. There was a
CLINICALCHEMISTRY, Vol. 34, No. 6, 1988 1029
creatinine clearance (r = -0.45, P <0.Oi). This suggests
that adequate dialysis should imply distinguishing between
accumulated solute groups that differ with respect to the
mechanism of excretion in intact nephrons. In its conse-quences this would be a different approach toaccounting for
remaining renal function, as isdone in the approach of a
“Dialysis Index” (28), which was proposed to model the so-called middle molecules. In that approach, a hypothetical
middle molecule ofMr i300 wasused, the removal of which
would benefit from any residual renal glomerular ifitration
(29), because the glomerulus filters these substances as
easily as low-molecular-mass solutes, which is not true for
the dialyzer membrane. Contrary to the hypothetical
non-measurable “middle molecule” (9, 30), now one of the
analytically well-defined organic acids, ormore specifically
hippurates, may be used as a measure of accumulation of
“organic-acid-like” substances.
It is an important observation that any residual renal
function contributes to the well-being of dialyzed patients,
whatever the precise explanation (31). Whether this is a
consequence of accumulation of tubularly secreted organic
acids in patients with negligible renal function remciins to
be established.
In conclusion, it seems worthwhile to introduce a marker for the accumulation of “organic-acid-like” compounds in
addition to urea (34). This could contribute to the goal of
“adequate dialysis” in the light of the proven toxicity of
these substances. p-Hydroxyhippuric acid or hippuric acid
might prove to be suitable. A choice should be based on
considerations of protein binding, measurability, single or
multipool kinetica, variation with diet, and (mode of)
endog-enous generation. In this perspective, the early work of
Smith et al. (26) and othersregains topicality.
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