274
Letters
those expected during angiography.
A well-defined peak was obtained in
the same zone of the ␣2 region in a
dose-dependent fashion. Appearance on AGE was unaffected by the
additions (Fig. 1). Iopamidol diluted
in CZE buffer solution displayed an
absorbance maximum of 242 nm as
described previously (2 ). The absorbance of iopamidol at 214 nm was
75% of the peak value, accounting for
its interference in the CZE analysis.
Interference of iodinated radioopaque contrast agents in CZE analysis of serum proteins has been described, with abnormal peaks in the
␣2, ␤, and prealbumin regions (2, 3 ).
Radio-opaque agents are usually
cleared rapidly from the serum; in
this case, clearance of iopamidol was
retarded by renal failure.
Clinicians may not be familiar
with the potential interference of radio-opaque contrast agents in CZE.
This may lead to diagnostic confusion in instances where blood for SPE
by CZE is taken soon after an imaging procedure or in patients in whom
renal clearance of contrast agent is
defective. With the widespread use
of CZE, this phenomenon may be
encountered more frequently, and
laboratories are urged not to discard
AGE methods entirely because they
have value in validating abnormal
peaks on CZE.
References
1. Bossuyt X, Schietekatte G, Bogaerts A, Blankaert N. Serum protein electrophoresis by CZE
2000 clinical capillary electrophoresis system.
Clin Chem 1998;44:749 –59.
2. Arranz-Peňa ML, González-Sagrado M, OlmosLinares AM, Fernández-Garcia N, Martin-Gil
FJ. Interference of iodinated contrast media in
serum capillary zone electrophoresis [Letter].
Clin Chem 2000;46:736 –7.
3. Bossuyt X, Mewis A, Blanckaert N. Interference
of radio-opaque agents in clinical capillary zone
electrophoresis [Technical Brief]. Clin Chem
1999;45:129 –31.
George van der Watt*
Peter Berman
Division of Chemical Pathology
Groote Schuur Hospital
University of Cape Town
Observatory
Cape Town, South Africa 7925
*Author for correspondence. Fax 02712-4044105; e-mail georgev@chempath.
uct.ac.za.
DOI: 10.1373/clinchem.2004.043505
Concentrations of Circulating
Gelatinases (Matrix
Metalloproteinase-2 and -9) Are
Dependent on the Conditions of
Blood Collection
To the Editor:
Matrix metalloproteinases (MMPs)
are a family of zinc endopeptidases
collectively capable of degrading essentially all components of the extracellular matrix. They are involved in
many physiologic and pathologic
processes, such as wound healing,
angiogenesis, embryo implantation,
cancer progression, and metastasis.
Several studies have measured circulating MMP-2 and -9 in cancer patients, but the results have been contradictory, specially for MMP-9, for
which very large patient-to-patient
variability was observed (1, 2 ). This
could be caused by different preanalytical conditions in blood sampling,
as suggested by recent studies (3– 6 ).
We studied the impact of blood sampling conditions on the measurement by ELISA of MMP-2 and -9.
This study was accepted by our Institutional Review Board, and written informed consent was obtained
from all volunteers participating in
the study.
In our first study, we collected
venous blood samples from 12
healthy volunteers into VacutainerTM
Tubes containing clot activator (SST),
lithium heparinate (LH), dipotassium EDTA, or sodium citrate. The
tubes were either centrifuged immediately (t0) or after 0.5, 2, or 24 h.
Tubes were left at room temperature,
except for the tubes that sat for 24 h,
which were kept at 4 °C. Measurements were performed within 5 days
of sampling, and plasma and sera
were stored at 4 °C until assayed.
In our second study, we collected
venous blood samples from four
healthy volunteers as described above
(except for serum). Cells and plasma
were immediately separated by centrifugation and aspiration. Cells were
then transferred to clean plastic tubes
containing a volume of sterile saline
equal to that of the original plasma.
Plasma and cells were incubated for
0.5 h, 2 h (room temperature) and 24 h
(4 °C). After incubation, plasma and
cell supernatants were stored at
⫺20 °C until assayed.
MMP-2 and -9 concentrations were
measured in plasma and serum samples by our own enzyme immunoassays (EIAs) (7 ). Results were confirmed by commercially available
assays (Biotrak; Amersham). Gelatinolytic activity was measured by
zymography as described previously
(8 ).
Statistical analyses were performed by ANOVA using the Fisher
test. P ⬍0.05 was considered as representing a statistically significant
difference.
In the first study, with the exception of citrate plasma, the concentration of immunoreactive MMP-9 increased with the time between
sampling and centrifugation (Fig.
1A). The effect of time was dependent on the type of anticoagulant,
however, being much more marked
in heparin plasma and serum compared with EDTA plasma. Furthermore, the mean (SE) measured concentration of MMP-9 in EDTA
plasma [55.4 (8.1 ␮g/L)] was significantly higher than in citrate plasma
[19.4 (3.5) ␮g/L; P ⫽ 0.0003], heparin
plasma [27.4 (3.1) ␮g/L; P ⫽ 0.0002],
or serum [32.6 (1.2) ␮g/L; P ⫽
0.0094].
We obtained similar results when
we measured the gelatinolytic activity of MMP-9 by zymography (results not shown), except that MMP-9
activity was significantly increased
after 2 h only in heparin plasma and
serum.
In sharp contrast to MMP-9, the concentration of immunoreactive MMP-2
did not increase with time between
sampling and centrifugation; in fact, it
was decreased in EDTA plasma after
2 and 24 h. The measured concentrations of MMP-2 were significantly lower
Clinical Chemistry 51, No. 1, 2005
275
Fig. 1. Effect of time between blood sampling and centrifugation on MMP-9 and -2 concentrations in plasma/serum measured by EIA (A), and effect
of time on the release of MMP-9 and -2 by the blood pellet in saline (B).
Values are the mean (SE; error bars). a, P ⬍0.05; b, P ⬍0.01, c, P ⬍0.001. (A), results are expressed as a percentage of the concentration at t0. (B), results are
expressed as a percentage of the concentration at t0.5.
in EDTA plasma [86.5 (15.6) ␮g/L]
than in citrate plasma [405.5 (54.3)
␮g/L;P⬍0.0001],heparinplasma[569.9
(26.5) ␮g/L; P ⬍0.0001], and serum
[610.6 (25.9) ␮g/L; P ⬍0.0001].
Addition of increasing concentration of EDTA (final concentration,
0.06 –1.8 g/L) to serum markedly reduced the measured concentration of
MMP-2, whereas it had no effect on
MMP-9 (results not shown).
In the second study, the concentration of MMP-9 released by blood
cells separated immediately from citrate, EDTA, and heparin plasma increased with the time of incubation
of the cells in saline (Fig. 1B). In
contrast, MMP-9 concentrations in
the plasmas (from which the cells
were isolated) incubated for the same
period of time did not change over
time (results not shown). MMP-2
concentrations also did not change
over time in the supernatant of incubated cells (Fig. 1B) or in plasma
(results not shown).
Preanalytical conditions affect circulating MMP-2 and -9 concentrations. Jung et al. (4 ) have shown, by
EIA, that MMP-9 was higher in serum than in heparin plasma and that
MMP-2 was lowered in the presence
of EDTA (3 ). Mannello et al. (5 )
showed by zymography that MMP-9
was higher in serum than in heparin
or citrate plasma and that addition of
EDTA decreased the concentrations
of MMP-2 and increased those of
MMP-9. Finally, Makowski et al. (6 )
showed by zymography that MMP-9
was higher in heparin and EDTA
plasma than in citrate plasma when
blood was left 1 h between sampling
and centrifugation.
Using a quantitative assay (EIA)
to measure the MMP concentrations,
we confirmed the differences between the anticoagulants and the
importance of controlling time between blood sampling and centrifugation. We showed that these differences are attributable to the
release of MMPs by blood cells. In
serum and heparin plasma, the release of MMP-9 is massive and timedependent, rendering any clinical
study impossible, whereas MMP-2 is
276
Letters
not affected. EDTA markedly decreases the concentration of MMP-2,
whereas it increases MMP-9. We conclude that citrate is the anticoagulant
of choice because it inhibits the release of gelatinases by blood cells in
the plasma and thus reduces the influence of time.
References
1. Riedel F, Gotte K, Schwalb J, Hormann K. Serum
levels of matrix metalloproteinase-2 and -9 in
patients with head and neck squamous cell
carcinoma. Anticancer Res 2000;20:3045–9.
2. Hayasaka A, Suzuki N, Fujimoto N, Iwama S,
Fukuyama E, Kanda Y, et al. Elevated plasma
levels of matrix metalloproteinase-9 (92-kd type
IV collagenase/gelatinase B) in hepatocellular
carcinoma. Hepatology 1996;24:1058 – 62.
3. Jung K, Laube C, Lein M, Lichtinghagen R,
Tschesche H, Schnorr D, et al. Kind of samples
as preanalytical determinant of matrix metalloproteinase 2 and 9 and tissue inhibitor of metalloproteinase 2 in blood. Clin Chem 1998;44:
1060 –2.
4. Jung K, Lein M, Laube C, Lichtinghagen R. Blood
specimen collection methods influence the concentration and the diagnostic validity of matrix
metalloproteinase 9 in blood. Clin Chim Acta
2001;314:241– 4.
5. Mannello F, Luchetti F, Canonico B, Papa S.
Effect of anticoagulants and cell separation media as preanalytical determinants on zymographic analysis of plasma matrix metalloproteinases. Clin Chem 2003;49:1956 –7.
6. Makowski GS, Ramsby ML. Use of citrate to
minimize neutrophil matrix metalloproteinase-9
in human plasma. Anal Biochem 2003;322:
283– 6.
7. Meisser A, Chardonnens D, Campana A, Bischof
P. Effects of tumor necrosis factor ␣, interleukin-1 ␣, macrophage colony stimulating factor
and transforming growth factor ␤ on trophoblastic matrix metalloproteinases. Mol Hum Reprod
1999;5:252– 60.
8. Martelli, M, Campana, A, Bischof, P. Secretion
of matrix metalloproteinases by human endometrial cells in vitro. J Reprod Fertil 1993;98:67–
76.
Arielle Meisser
Marie Cohen
Paul Bischof*
Department of Obstetrics
and Gynaecology
University of Geneva
Geneva, Switzerland
*Address correspondence to this author at: Laboratoire d’Hormonologie, Maternité, 1211 Geneva 14, Switzerland.
Fax 41-22-382-4310; e-mail paul.bischof@
hcuge.ch.
DOI: 10.1373/clinchem.2004.041707
Calculation of Measurement
Uncertainty in Clinical Chemistry
To the Editor:
Patriarca et al. (1 ) recently presented
in this journal “a working example”
for the calculation of measurement
uncertainty (lead in blood) according
to the rules of the ISO Guide to the
Expression of Uncertainty in Measurement (GUM) (2 ). Although the authors presented many estimates of
imprecision and trueness, they failed
to correctly combine the estimates.
They estimated the overall long-term
SD from quality-control samples
(SDcontrol) and from human samples
(SDhuman) and combined them by
taking the “square root of the sum of
the squares”. Instead, however, they
should have used the pooled SD of
both estimates, to be calculated as:
SDpooled
冋
册
2
(ncontrol ⫺ 1) ⫻ SDcontrol
2
⫹ (nhuman ⫺ 1) ⫻ SDhuman
⫽
(ncontrol ⫹ nhuman ⫺ 2)
0.5
with n the number of samples. They
presented four estimates of trueness,
i.e., measurement of certified reference materials (CRMs), recovery, and
results from two external quality assessment surveys (EQAs) and combined them into one mean index
(Rm), disregarding the fact that the
estimates conflicted with each other
and were dependent on the concentration of lead.
Generally, one should not use second- (recovery) or third-choice estimates (EQA results with poorly defined target values) for the
uncertainty calculation when one has
available first-choice estimates (comparison with CRMs). Consequently,
from the data presented, we would
conclude that the method is bias-free
in the high concentration range
(⬃130 ␮g/L), has a considerable bias
in the mid concentration range (⬃40
␮g/L), and has an unknown bias in
the low range (less than ⬃30 ␮g/L).
Moreover, we question their approach of including a bias in an uncertainty calculation [square root of
the sum of the squares of imprecision
and trueness components; note that
for estimation of the trueness compo-
nent they used a rather uncommon
procedure, as described by Barwick
and Ellison (3 )]. Although many believe this is the approach recommended by GUM for treating a bias,
it is not. GUM encourages the analyst
to search for the cause of a bias and
to correct it. This is what the authors
should have done.
As long as the cause for the bias
remains unknown, it may be prudent
to report results in the low concentration range as, for example, ⬍25
␮g/L. In addition, if a bias is considered small compared with the overall
uncertainty, it simply may be neglected. Furthermore, in exceptional
cases (“the small letters of GUM”), a
bias may be included in the expanded uncertainty (U) as U ⫹ bias
[point F.2.4.5 on page 57 of GUM (2 ),
and point 2.5.8 (treatment of uncorrected bias) in the NIST/SEMATECH
e-Handbook of Statistical Methods (4 )].
We want to mention that, different
from the GUM, there is a tradition of
squaring of bias in the statistical literature (5 ), e.g., for calculating the
root mean squared error (RMSE)
used to rank competing statistical
estimation procedures (RMSE ⫽
公bias2 ⫹ SE2).
References
1. Patriarca M, Castelli M, Corsetti F, Menditto A.
Estimate of uncertainty of measurement from a
single-laboratory validation study: application to
the determination of lead in blood. Clin Chem
2004;50:1396 – 405.
2. International Organization for Standardization.
ISO guide to the expression of uncertainty in
measurement. Geneva: ISO, 1995.
3. Barwick JV, Ellison SLR. The evaluation of measurement uncertainty from method validation
studies. Accred Qual Assur 2000;5:47–53.
4. NIST/SEMATECH. NIST/SEMATECH e-handbook
of statistical methods. http://www.itl.nist.gov/
div898/handbook (accessed August 2004).
5. Taylor JR, ed. An introduction to error analysis:
the study of uncertainties in physical measurements. Mill Valley, CA: University Science
Books, 270pp.
Dietmar Stöckl
Katleen Van Uytfanghe
Diego Rodrı́guez Cabaleiro
Linda M. Thienpont*
Laboratorium voor Analytische Chemie
Faculteit Farmaceutische
Wetenschappen
Universiteit Gent
Harelbekestraat 72
B-9000 Gent, Belgium