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Serum levels of matrix metalloproteinase 3 and macrophage colony-stimulating factor 1 correlate with disease activity in ankylosing spondylitis.

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Arthritis & Rheumatism (Arthritis Care & Research)
Vol. 51, No. 5, October 15, 2004, pp 691– 699
DOI 10.1002/art.20696
© 2004, American College of Rheumatology
ORIGINAL ARTICLE
Serum Levels of Matrix Metalloproteinase 3 and
Macrophage Colony-Stimulating Factor 1
Correlate With Disease Activity in Ankylosing
Spondylitis
CHUNHUA YANG,1 JIERUO GU,1 MARKUS RIHL,1 DOMINIQUE BAETEN,2 FENG HUANG,3
MIANSONG ZHAO,3 HANWEI ZHANG,1 WALTER P. MAKSYMOWYCH,4 FILIP DE KEYSER,5
ERIC M. VEYS,5 AND DAVID T. Y. YU1
Objective. To assess the usefulness of measuring serum matrix metalloproteinase 3 (MMP-3) and macrophage colonystimulating factor (M-CSF) in patients with ankylosing spondylitis (AS).
Methods. Serum levels of MMP-3 and M-CSF were measured in AS patients who did and did not receive infliximab
treatment. These were compared with those of 28 healthy subjects.
Results. In the group of AS patients not treated with biologics, both M-CSF and MMP-3 correlated with the Bath
Ankylosing Spondylitis Disease Activity Index (BASDAI) values, but not with each other. Logistic regression analysis
showed that MMP-3 values were high in those with severely active disease. Infusions of infliximab in AS patients led to
a significant decrease in the values of the BASDAI as well as the serum MMP-3, but no change in the serum M-CSF values.
Conclusion. MMP-3 and M-CSF are potentially useful markers of AS disease activity.
KEY WORDS. MMP-3; M-CSF-1; Ankylosing spondylitis; BASDAI; Infliximab.
INTRODUCTION
Despite decades of intense research, the molecular pathways that mediate the spondylarthropathies are still completely unknown. Although HLA–B27 is a contributing
factor, how it initiates arthritis remains controversial. No
universally accepted hypothesis is available to allow investigators to pursue an infallible hypothesis-driven approach. What is clear is that there are multiple genetic
The work of Drs. Yang, Gu, Rihl, Yu, and Zhang is supported by the Nora Eccles Treadwell Foundation. The work
of Drs. Huang and Zhao is supported by the National Natural Science Foundation of China, grant # 30025041.
1
Chunhua Yang, MD, Jieruo Gu, MD, Markus Rihl, MD,
Hanwei Zhang, MSc, David T. Y. Yu, MD: University of
California Los Angeles; 2Dominique Baeten MD: University
of Ghent, Ghent, and Fund for Scientific Research-Flanderen (FWO-Vlaanderen), Belgium; 3Feng Huang, MD, Miansong Zhao, MD: Chinese PLA General Hospital, Beijing,
China; 4Walter P. Maksymowych, FRCP(C): University of
Alberta, Edmonton, Alberta, Canada; 5Filip De Keyser, MD,
Eric M. Veys, MD: University of Ghent, Ghent, Belgium.
Address correspondence to David Yu, 35-40 Rehabilitation Center, Rheumatology Division, 1000 Veteran Avenue,
Los Angeles, CA 90095. E-mail: dtyyu@ucla.edu.
Submitted for publication October 14, 2003; accepted in
revised form February 9, 2004.
factors, and there must be many more critical factors other
than HLA–B27 (1). Hence, identifying these factors would
be critical to this field of research. Since the identities of
some of these factors are probably beyond our imagination,
one reasonable approach is to use microarrays to randomly
screen for genes differentially expressed in spondylarthropathy (SpA) tissues. In this article, we use a 1,176 gene
microarray to study SpA synovial tissues.
There are two challenges in using microarrays for this
purpose. The first is to be able to follow stringent guidelines for reproducibility so that the results are not simply
a massive amount of uninterpretable information. In this
article, we have set up strict criteria for selection of candidate transcripts, taking into account variability among
duplicate assays, power analysis to predict sample sizes,
comparison of variance for appropriate use of parametric
or nonparametric analysis, and statistical correction when
comparing multiple genes. By employing these strategies,
we identified 3 candidates in our microarray results: macrophage colony-stimulating factor (M-CSF), matrix metalloproteinase 3 (MMP-3), and interleukin 7 (IL-7).
The second challenge in microarray is that tissue samples consist of heterogeneous cell types, so that the aboveidentified genes might appear to be highly expressed only
because certain cell types are preferentially enriched. To
691
692
Yang et al
Table 1. Characteristics of patients providing synovial
biopsy samples*
Designation
no.
Sex
Age,
years
Diagnosis
HLA–B27
1
2
3
4
5
6
7
8
9
10
11
F
M
M
M
F
F
M
M
M
M
M
21
39
44
54
18
34
66
53
43
54
39
USpA
AS
AS
PsA
SpA with IBD
SpA
AS
AS
AS
USpA
AS
Pos
Pos
Pos
Neg
Pos
Neg
Pos
Pos
Pos
Neg
Pos
* uSpA ⫽ undifferentiated spondylarthropathy; Pos ⫽ positive;
AS ⫽ ankylosing spondylitis; PsA ⫽ psoriatic arthritis; Neg ⫽
negative; SpA ⫽ spondylarthropathy; IBD ⫽ inflammatory bowel
disease.
ensure that the candidates uncovered by microarray are
participants in the disease processes, we arbitrarily postulate that any observed microarray transcripts will be acceptable as candidates only if the serum concentrations
of the corresponding proteins correlate with the disease
activity index. In this way, we bypass even the step of
verification of expression of candidate transcripts by reverse transcriptase–polymerase chain reaction (PCR). This
is because, regardless of whether they are false positives
of the microarrays, such candidates are still promising
targets for future research. Equally important, their serum
concentrations might also help us to assess SpA disease
activity.
We collected 2 sets of serum samples for this purpose.
The first set was derived from 41 ankylosing spondylitis
(AS) patients in Beijing. The characteristics of these patients have been carefully recorded, including scores for
Bath Ankylosing Spondylitis Disease Activity Index
(BASDAI) (2) and Bath Ankylosing Spondylitis Functional
Index (BASFI) (3). Using these samples, we tested if serum
levels of MMP-3 and M-CSF would correlate with the
BASDAI values. This was indeed the case. The second set
of serum samples consists of 13 of 21 previously reported
AS patients in Edmonton, Canada (4). These are paired
samples from patients before and 14 weeks after initiation
of infliximab infusions. Infliximab is an anti-tumor necrosis factor (anti-TNF) antibody that, in the majority of AS
patients, provides suppression of signs and symptoms
(5,6). We postulated that if our observed genes were relevant to the disease, the serum concentrations of the encoded proteins would be suppressed by infliximab infusions. This is indeed the case with MMP-3.
SUBJECTS AND METHODS
Clinical materials. For microarrays, synovial biopsy
samples were obtained from 11 SpA patients during needle arthroscopy, as reported previously (7). Demographics
of these patients are summarized in Table 1. Peripheral
blood mononuclear cells (PBMCs) of 10 healthy subjects
(age 31–59 years, 3 female, 7 male) provided microarray
controls. Six of these healthy subjects were white and 4
were Asian. For an enzyme-linked immunosorbent assay
(ELISA), serum samples were obtained from AS patients:
41 from Beijing and 13 pair samples from Edmonton. For
the Edmonton patients, serum samples were collected before and 14 weeks after the start of infliximab infusions.
Infliximab was administered at 3 mg/kg at weeks 0, 2, and
6 (4). The Beijing patients had not been treated with any
anti-TNF agents or thalidomide or methotrexate. Twentyeight healthy subjects from Beijing (age 15– 49 years, 14
female, 14 male) provided control serum samples. Synovial fluid samples were obtained by arthrocentesis from 15
SpA patients with synovial effusions. Eight of these patients were diagnosed as having AS, 6 as having undifferentiated spondylarthropathy (USpA), and 1 as having reactive arthritis. These procedures and their consent forms
were approved by the respective institutes. Diagnosis of
AS and SpA followed standard criteria (8).
Microarrays. The methods for microarray assay followed those provided by BD Biosciences Clontech (Palo
Alto, CA) and have been reported previously (8). Briefly,
RNA was extracted from tissue and cell samples by solution D (Strategene, LaJolla, CA) and purified by repeated
phenol:chloroform reextractions. RNA (150 ng) was then
amplified by SMART-PCR (BD Biosciences Clontech), the
cycle numbers being monitored to avoid amplification beyond the exponential phase. Amplified complementary
DNA (cDNA) was labeled with 33P-dCTP using rediprime
II random prime labeling system (Amersham, Piscataway,
NJ) and hybridized to a cDNA-based nylon membrane
(Atlas Human 1.2 array; BD Biosciences Clontech). After
exposure to a phosphor screen, signals were scanned and
recorded with a STORM scanner (Molecular Dynamics,
Sunnyvale, CA). Signal intensities were computed by the
AtlasImage 1.5 software (BD Biosciences Clontech). For
each gene, local background intensity value was subtracted from the gross intensity value. When results of one
membrane were compared with those of another, the intensities of the genes in both membranes were normalized
to the mean intensities of glyceraldehyde-3-phosphate dehydrogenase. Calculation of threshold and statistical evaluation will be described in the Results section.
ELISA. ELISA kits were purchased from commercial
sources: Human M-CSF Immunoassay (R&D Systems, Minneapolis, MN), Human Matrix Metalloproteinase-3 Biotrak
ELISA system (Amersham), Human IL-7 ELISA kit (Cell
Sciences, Norwood, MA), and Human Tissue Inhibitor of
Metalloproteinase-2 BioTrak ELISA system (Amersham).
All assays were carried out in duplicate and followed the
manufacturers’ recommendations. The MMP-3 ELISA kit
measures total MMP-3 including pro-MMP-3, active
MMP-3, and MMP-3/tissue inhibitor of metalloproteinase
(TIMP) complexes. The M-CSF kit utilizes recombinant
158 amino-terminal amino acid residues of the extracellular domain of native M-CSF.
Serum MMP-3 and M-CSF-1 in Ankylosing Spondylitis
Figure 1. Extent of variability in microarray. Number of genes
with variability exceeding the background values shown on the
x-axis. The broken line represents results from the peripheral
blood mononuclear cell (PBMC) in duplicate. The solid line represents results from the lipopolysaccharide-stimulated PBMC in
duplicate.
Statistics. Statistical evaluations were carried out with
Microsoft (Redmond, WA) Excel and the XLStat software
(available at URL: http://www.xlstat.com).
RESULTS
Results of microarrays. In the first preliminary experiment, the variability of the microarray technique was assessed by analyzing duplicate experiments of 2 different
samples: 1 was a PBMC sample, the other a lipopolysaccharide-stimulated PBMC (LPS-PBMC) sample. The 2
were included because they provided different numbers of
genes in which the intensity values exceeded the background values (149 in PBMC versus 204 in LPS-PBMC).
Within each replicate, the extent of variability in intensity
signal for each of the 1,176 genes was calculated. Because
the absolute intensity signal for each gene also depends on
the background intensity, the variability values were expressed as a ratio of the corresponding background intensities. In the duplicate PBMC samples, the number of
genes with variability exceeding 1⫻, 2⫻, 3⫻, 4⫻, and 5⫻
background values were 48, 12, 2, 1, and 0, respectively. In
the LPS-activated samples, they were 6, 2, 0, 0, and 0,
respectively (Figure 1). This suggested that there would be
only a very small margin of error if we take into consideration only those genes in the SpA samples that exceed the
control samples by more than 3 times the background
values.
In the second preliminary experiment, the microarray
results of 5 different PBMCs from healthy adult subjects
were compared with those of 6 different SpA tissue samples. In this and subsequent experiments, variance was
compared by the F test before deciding whether the parametric or the nonparametric tests should be used. Using
the t-test, the gene that showed the highest degree of statistical significance between the 2 groups was neurotrophin 4. However, the P value was only 0.005. Using the
Bonferroni correction for multiple comparisons, a P value
of 0.000042 was needed for actual statistical significance.
A power analysis was then carried out using Statmate
693
software (GraphPad Softwares, San Diego, CA). It indicated that the number of samples for each group should be
increased to at least 8. The numbers of samples for PBMC
and for SpA tissue were then increased to 10 and 11,
respectively. Again, for each gene in the microarray, the
mean value of the 10 PBMCs was compared with the mean
value of the 11 SpA tissue samples. Taking the Bonferroni
correction into consideration, only 1 gene showed results
of statistical significance, with P ⫽ 0.000007. This was the
M-CSF (mean ⫾ SD of PBMC and SpA tissue samples:
3,234 ⫾ 3,848 and 23,588 ⫾ 8,832; values are intensity
measurements of microarray results).
Many genes provided in the microarray membranes did
not generate intensity signals exceeding the background. If
the Bonferroni correction for multiple comparisons takes
into account only those genes with positive intensity signals, 3 additional genes met the threshold. They were IL-7,
MMP-3, and Bcl-xL/Bcl-2–associated death promoter
(BAD) protein (P ⫽ 0.0003 for all 3 genes). Mean ⫾ SD
values of PBMC and SpA tissue samples were 1,325 ⫾
1,711 and 16,106 ⫾ 9,356 for IL-7, 100 ⫾ 260 and 23,155 ⫾
14,430 for MMP-3, and 1,866 ⫾ 2,030 and 20,672 ⫾ 11,961
for BAD protein). The neurotrophin gene was identified
using the smaller number of samples to calculate power
analysis and was ranked to the next highest statistical
significance (P ⫽ 0.001).
Taking the intensity threshold determined in the first
preliminary experiment into consideration (Figure 1), the
4 genes with the lowest P values listed above showed high
likelihood of being true positives. Of the 4 genes identified, protein levels of the first 3 can be measured by ELISA.
Clinical parameters of a cohort of AS patients and their
serum levels of M-CSF, MMP-3, and IL-7. We recruited 41
AS patients attending a specialty clinic in Beijing. None of
these patients were treated with biologics. Nine of the 41
patients were female. The mean ⫾ SD age of the 41 patients was 25 ⫾ 9.9 years and disease duration was 62.4 ⫾
70.4 months. The mean ⫾ SD value for the BASDAI was
5.3 ⫾ 0.24, with the median being 5.25 (Table 2). There is
a significant correlation of the BASDAI with the erythrocyte sedimentation rate (ESR; r ⫽ 0.54, P ⫽ 0.0001; n ⫽ 41;
Figure 2 lower panel) and the BASFI (r ⫽ 0.27, P ⫽ 0.05;
n ⫽ 41; Figure 2, upper panel), but not with the C-reactive
protein (CRP; r ⫽ 0.22, P ⫽ 0.1). However, in only 35 of the
41 patients was CRP measured. Because of this limitation,
the potential clinical value of CRP was not analyzed in
subsequent experiments. For BASFI, there is a significant
correlation with BASDAI (r ⫽ 0.27, P ⫽ 0.05), finger to
floor distance (r ⫽ 0.43, P ⫽ 0.003), and occiput to wall
distance (r ⫽ 0.27, P ⫽ 0.043), but not with duration of
disease, age, Schober measurement, ESR, or CRP.
Serum levels of IL-7 were undetectable. For M-CSF, the
serum levels in the 41 AS patients ranged from 398 to
3,833 pg/ml (Tables 2 and 3). There is no significant difference in the mean serum M-CSF levels between these 41
AS patients and 28 healthy subjects. We also collected
synovial fluid samples from 8 patients with AS, 6 patients
with USpA, and 1 patient with reactive arthritis. There is
no statistically significant difference between the synovial
20
18
24
28
37
18
40
30
30
20
15
38
26
24
32
20
20
14
12
12
53
14
13
17
34
21
22
32
42
12
19
19
20
30
26
21
30
30
12
40
41
F
M
F
M
F
M
M
F
M
M
F
M
M
M
M
M
M
M
F
F
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
F
M
M
F
24
6
60
120
12
2
11
120
86
72
2
216
108
72
168
2
60
24
132
14
72
12
60
108
72
9
24
36
348
12
2
12
36
96
24
96
168
24
12
2
24
Pos
Pos
Pos
Pos
Neg
Pos
Neg
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Neg
Neg
Neg
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Pos
Neg
Pos
Pos
Pos
Neg
Pos
Neg
Pos
Pos
Neg
HLA–
B27
2
4
3
14
10
10
10
10
10
5
0
3
5
10
10
13
0
10
10
10
10
15
15
10
15
10
10
8
50
10
10
15
0
10
10
10
15
10
10
15
8
Occiputto-wall,
cm
2.5
3
2.5
3
2
4
4
3
2
5
3
2
3
2
3
4
2
3
3
4
2
4
4
5
4
7
4
7
2
7
7
7
7
5
5
4
4
4
4
4
2
0
10
10
10
50
0
0
20
10
3
15
20
20
30
20
10
30
15
30
8
10
50
50
20
50
15
50
4
50
8
8
8
8
10
10
10
15
10
10
50
50
5
1
3
5
0
5
5
3
–
5
5
3
2
4
5
5
4
4
5
5
4
4
4
5
4
5
5
4
5
5
5
5
5
4
5
4
4
4
4
4
0
4.6
10.6
6.5
5.6
5.7
4.5
6.8
10.3
5.5
6.3
7.6
7
6.3
10.5
10.8
6.1
4.5
8.6
7.5
4.3
8.6
13.7
10.7
3.3
4.6
5.4
10.1
5.2
5.4
6.2
5.4
6.3
9.4
10.2
8.2
5.6
6.2
5.8
11.5
7.8
10.3
113
331
105
145
325
329
181
322
303
312
187
398
142
243
303
312
245
220
217
330
165
336
402
527
534
178
445
212
242
233
243
252
323
124
154
163
145
165
621
335
455
2.85
6
3.3
2.4
5.2
2.5
0.8
7.6
7.1
6.2
3.7
4.2
4.9
3.5
4.9
4.9
4.5
5.4
4.2
4.9
6.2
7
5.9
7.7
5.6
5
6.6
1.8
5.4
3.9
3.9
4.9
2.3
3.95
5
6.55
6.7
7.4
7.2
4.4
8.8
2.9
5.6
1.85
5.2
4.5
4.8
3.8
6.9
6.5
6.4
7.2
5.4
6.2
4.7
6.4
7.05
4.55
4.65
4.05
5.7
5.3
6.1
8.2
5.5
5.15
6.75
4.85
3.35
4.4
3.8
2.95
5.25
4.35
6.25
5.15
3.7
6.5
6.3
7.75
3.7
9.6
15
62
33
28
16
69
23
32
24
25
87
28
25
24
20
75
13
8
32
45
15
44
22
65
78
78
70
45
12
12
21
16
22
20
13
16
78
19
73
65
110
2.3
4.5
2.3
2.6
0.61
0.65
1.32
2.3
1.2
2
1.2
0.98
1
0.78
0.79
5.6
1.12
7.8
0.2
1.2
7.48
2.89
3.5
2.3
0.8
2.1
3.2
2.5
1.2
3.7
0.98
1.85
1.2
0.4
0
0
87.5
707
0
0
20.3
19.2
1.4
11.2
30.1
49.6
18.6
99.5
22.6
58.8
127.7
15.7
0
18
24.9
24.9
16.3
22.1
18.6
31.2
48.4
61.1
27.2
6
0
6
8.9
16.3
30.7
70.3
37.5
76.6
15.7
23.8
17.5
175.8
638
848
457
1,320
398
1,477
885
913
1,053
922
2,239
1,553
3,473
2,972
3,017
1,663
1,157
1,603
1,374
1,594
1,374
2,065
3,833
1,523
3,560
3,315
3,259
787
1,025
1,642
868
2,836
1,051
792
1,598
718
1,188
679
1,741
738
729
42.5
78.5
39.1
47.0
44.2
73.0
40.9
41.2
50.3
40.8
34.1
39.4
51.5
37.0
113.4
39.6
33.3
42.3
37.7
40.3
39.1
32.1
36.5
34.9
39.9
37.6
71.5
33.4
34.8
38.6
32.8
34.7
38.6
33.7
34.1
33.6
41.1
40.2
35.9
34.6
38.2
Chest
ESR,
expansion, Finger-to- Schober’s
Platelet/
mm/1st
MMP-3, M-CSF, TIMP-2,
cm
floor, cm
test
WBC/ml
ml
BASFI BASDAI hour CRP ng/ml
pg/ml
ng/ml
* WBC ⫽ white blood cell count; BASFI - Bath Ankylosing Spondylitis Functional Index; BASDAI ⫽ Bath Ankylosing Spondylitis Disease Activity Index; ESR ⫽ erythrocyte sedimentation rate; CRP ⫽
C-reactive protein; MMP-3 ⫽ matrix metalloproteinase 3; M-CSF ⫽ macrophage colony-stimulating factor; TIMP-2 ⫽ tissue inhibitor of metalloproteinase 2; Pos ⫽ positive; Neg ⫽ negative.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Disease
Patient Age,
duration,
no.
years Sex months
Table 2. Clinical and enzyme-linked immunosorbent assay data of 41 ankylosing spondylitis patients*
694
Yang et al
Serum MMP-3 and M-CSF-1 in Ankylosing Spondylitis
695
Figure 2. Correlation of Bath Ankylosing Disease Activity Index
(BASDAI) with A, Bath Ankylosing Spondylitis Functional Index
(BASFI) or B, with erythrocyte sedimentation rate (ESR) in 41
ankylosing spondylitis patients. Details of the 41 patients are
shown in Table 2.
fluid levels of M-CSF and the serum levels of the AS
patients or the healthy subjects (Table 3).
The MMP-3 serum levels of 41 AS patients ranged from
0 to 176 ng/ml (Table 2). The MMP-3 levels in the 15 SpA
synovial fluids on the other hand are more than 4 times
higher than the serum levels of the AS patients or the
healthy subjects (P ⬍ 0.000000008; Table 3). There is no
statistically significant difference in the serum MMP-3 levels between the 41 AS patients and the 28 healthy subjects.
Relationship between levels of M-CSF and MMP-3 with
clinical parameters. When compared with the various
clinical parameters shown in Table 2, there is a significant
Table 3. Serum and synovial fluid levels of M-CSF
and MMP-3*
Sample
M-CSF
SpA synovial fluid
AS serum
Healthy serum
MMP-3
SpA synovial fluid
AS serum
Healthy serum
n
mean ⴞ SD
15
41
28
974 ⫾ 879
1,582 ⫾ 952
1,407 ⫾ 892
15
41
28
2,177 ⫾ 602†
49.9 ⫾ 111.4
35.1 ⫾ 32.8
* M-CSF ⫽ macrophage colony-stimulating factor; MMP-3 ⫽ matrix
metalloproteinase 3; SpA ⫽ spondylarthropathy; AS ⫽ ankylosing
spondylitis.
† P ⫽ 0.0000000015 compared with serum levels.
Figure 3. Correlation of serum macrophage colony-stimulating
factor (M-CSF) levels with A, Bath Ankylosing Disease Activity
Index (BASDAI) or B, with serum matrix metalloproteinase 3
(MMP-3) levels in the 41 ankylosing spondylitis patients shown
in Table 2.
correlation between the levels of M-CSF and BASDAI (r ⫽
0.41, P ⫽ 0.004; Figure 3 upper panel). There is a weak
correlation with the platelet count (r ⫽ 0.25, P ⫽ 0.05), but
not the white blood cell count. There is no correlation
between M-CSF and other clinical parameters listed in
Table 2, including ESR (r ⫽ 0.2, P ⫽ 0.1).
As for serum levels of MMP-3, when compared with the
clinical parameters shown in Table 2, there is high correlation with ESR (r ⫽ 0.54, P ⫽ 0.0001) and with BASDAI
(r ⫽ 0.48, P ⫽ 0.0007; Figure 4). There is no significant
correlation with CRP or other clinical parameters listed in
Table 2. Although serum levels of MMP-3 and M-CSF
correlate with BASDAI, they do not correlate with one
another (r ⫽ 0.2, P ⫽ 0.1; Figure 3 lower panel). Twentyeight of the 41 AS patients showed peripheral arthritis in
having both swelling and tenderness in the joints peripheral to the spine, shoulders, and hips. However, when
analyzed by logistic regression, there was no correlation
between the levels of MMP-3 or M-CSF with the presence
of peripheral arthritis.
As a control, we also measured the serum level of
696
Yang et al
Table 4. Logistic regression analysis of disease severity
in comparison with other parameters*
Parameter
␹2
P
MMP-3
M-CSF
ESR
CRP
4.9
0.9
4.1
2.0
0.025
0.30
0.04
0.16
* Median of Bath Ankylosing Spondylitis Disease Activity Index
was used as the cutoff to determine whether disease was severely
active. MMP-3 ⫽ matrix metalloproteinase 3; M-CSF ⫽ macrophage
colony-stimulating factor; ESR ⫽ erythrocyte sedimentation rate;
CRP ⫽ C-reactive protein.
Figure 4. Correlation of serum matrix metalloproteinase 3
(MMP-3) levels with A, Bath Ankylosing Disease Activity Index
(BASDAI) or with B, erythrocyte sedimentation rate (ESR) in the
41 ankylosing spondylitis patients shown in Table 2.
TIMP-2. In our microarray study, this metalloproteinase
inhibitor was not found to be increased in the SpA tissue
samples. The serum levels of TIMP-2 in the 41 AS patients
ranged from 32.1 to 113.4 ng/ml (mean ⫾ SD 43 ⫾ 15.4).
There is no statistically significant correlation between
serum TIMP-2 levels and BASDAI (r ⫽ 0.1, P ⫽ 0.29),
BASFI (r ⫽ 0.07, P ⫽ 0.3), or ESR (r ⫽ 0.1, P ⫽ 0.3).
Next, we tested the value of combining several parameters to assess disease activity. Using multiple regression
analysis, we tested if there was a linear relationship model
in which values of ESR, BASFI, MMP-3, and M-CSF all
together would account for the variability of the BASDAI
values. With the combined values of ESR and BASFI, the
r2 value was 0.46. When values of MMP-3 and M-CSF were
added, the r2 value was improved to 0.57. Hence, 57% of
the variability of the BASDAI could be accounted for by
the combination of ESR, BASFI, MMP-3, and M-CSF.
In the above analysis, disease activity was considered as
a continuous variable. Using a predesigned BASDAI value
as cutoff, one can also divide patients qualitatively into
those with severe or mild disease. In the 41 patients in
Table 2, the median BASDAI value was 5.25. We then
arbitrarily grouped those with BASDAI values exceeding
this median value as having severely active disease. Using
univariate logistic regression analysis, we tested how well
the laboratory measurements ESR, CRP, MMP-3, and MCSF would correctly classify the patients into the categories of severe and mild disease. As shown in Table 4, ESR
and MMP-3 were almost the same in chi-square values.
Their P values were 0.04 and 0.025, respectively.
Effect of infliximab infusions on serum MMP-3, M-CSF,
and IL-7. Serum from 13 Canadian AS patients were examined for the effect of infliximab infusions on serum
M-CSF, MMP-3, and IL-7. The serum MMP-3 levels of 10
of these patients have been reported previously (4). The
current data are completely new measurements of these
patients. Patient characteristics are shown in Table 5. This
is a subset of 21 patients whose response to infliximab has
been reported previously. Only 13 patients were used in
the present study because they were the only ones in
which serum samples were still available. These 13 patients received infusions of 3 mg/kg of infliximab at weeks
0, 2, and 6. Measurements were carried out before infusion
and also at week 14. In these 13 patients, the BASDAI
scores decreased significantly from 6.4 ⫾ 1.5 at week 0 to
3 ⫾ 2.1 at week 14 (P ⫽ 0.00007 by paired t-test; Figure 5,
upper panel). In only 2 subjects was there no clinical
response, in that the decrease in BASDAI scores were
either ⬍2.0 or ⬍20% of values before infusion. When we
measured the serum MMP-3 levels of these 13 patients,
there was a statistically significant decrease in MMP-3 at
week 14 (P ⫽ 0.013 by Wilcoxon matched-pairs signedranks test; Figure 5 middle panel). For samples taken before infliximab infusion, there was a high degree of correlation between MMP-3 and ESR (r ⫽ 0.74, P ⫽ 0.002) and
CRP (r ⫽ 0.65, P ⫽ 0.008). The correlation became insignificant for samples taken after the infliximab infusions.
There was no statistical relationship between changes in
BASDAI values and changes in MMP-3. ESR, CRP, and the
serum levels of MMP-3 taken before the infusions were not
predictive of an absence of clinical response to the antiTNF agent. There was no statistically significant difference
of M-CSF serum levels before and after infliximab (Figure
5 lower panel).
DISCUSSION
Other than genome scanning and microarray screening,
most research effort on the spondylarthropathies have
been narrowly focused because they are hypothesis
driven, and so limited by the availability of candidate
causative factors (1). Our random screening has generated
2 research candidates that are relatively new to the field of
SpA: MMP-3 and M-CSF.
MMP-3 has been an subject of intense study in inflammatory arthritis conditions, especially rheumatoid arthri-
Serum MMP-3 and M-CSF-1 in Ankylosing Spondylitis
697
Table 5. Characteristic of ankylosing spondylitis patients on infliximab*
Designation
no.
Sex
Age,
years
Concommitant
conditions
1
2
3
4
5
6
7
8
9
10
11
12
13
M
F
F
M
M
M
M
F
M
M
M
M
M
26
39
60
55
35
53
51
38
40
31
49
48
31
PA, PsA
PA, PsA
PA, psoriasis
PA PsA
PA
PA
PA
Crohn’s
Crohn’s
Previous
DMARD
Pamidronate
Pamidronate
MTX, gold
MTX, HCQ, SSZ
MMP-3 before
infusions
MMP-3 after
infusions
220
51
142
25
188
42
27
35
22
1,221
19
125
113
51
14
14
22
102
57
36
18
26
394
13
42
43
* DMARD ⫽ disease-modifying antirheumatic drug; MMP-3 ⫽ matrix metalloproteinase; PA ⫽ peripheral arthritis; PSA ⫽ psoriatic arthritis; MTX ⫽
methotrexate; HCQ ⫽ hydroxy chloroguine; SSZ ⫽ sulfasalazine.
tis (RA) (9). One example is a study that prospectively
collected monthly serum MMP-3 measurements for 3 years
in 33 patients with early RA. Ribbens et al discovered that
the serum MMP-3 levels correlate with swollen joint
counts, RA disease activity scores, ESR, CRP, and outcome
of radiologic joint space narrowing (9). In contrast to RA,
very few SpA studies address the significance of serum
MMP-3. This is probably because the mean level of serum
MMP-3 in SpA is within the range of normal subjects, as
observed in this study (10,11).
There are at least 3 observations in our results that are
remarkable. The first observation is that MMP-3 levels are
much higher in synovial fluids compared with serum samples. This would indicate that there is high expression of
the MMP-3 protein in the joints. Interestingly, MMP-3 has
also been reported to be highly expressed in discs of the
spine (12), a target of SpA disease process. Being generated
in the articular areas, measurements of serum MMP-3
would in theory reflect more closely the events at the joints
compared with those markers generated elsewhere, such
as ESR or CRP. Our second new observation is that there is
a certain degree of correlation between serum MMP-3 levels and disease activity. Measuring disease activity has
always been a challenge in SpA. The standard measurement, the BASDAI, consists of a number of question-based
scale evaluations (2). It is completely subjective. In the
case of those 41 Beijing patients we studied, it probably
has a certain degree of reliability because there is a correlation of the BASDAI values with the values of the functional impairment index. ESR and CRP are objective measurements, and have been used as adjuncts in evaluating
disease activity of several inflammatory rheumatic diseases. In our 41 patients, the BASDAI values do correlate
with ESR. However, at least 2 studies have found ESR and
CRP to be questionable measurements of SpA disease activity (13,14). Our discovery that there is a certain degree
of correlation between serum MMP-3 levels and BASDAI
would indicate that it could be studied as another objective parameter of measurement of disease activity. Accurate assessment of AS disease activity has become very
important in clinical practice. Many patients with active
AS will respond favorably to treatment with etanercept or
infliximab, as we reported here. Because of the high cost of
the drugs, it is important to generate an accurate method to
measure disease activity to ensure that a particular patient
does have a favorable response to the drugs. Our third
observation here addresses this problem. Similar to what
one of us have reported with a smaller subset of this same
group of patients (4), and also in RA (15), we confirmed
that infliximab infusions did induce a significant decrease
in MMP-3 levels. Our 3 findings with MMP-3 would
strongly indicate that it should be studied as a measurement of disease activity, especially during treatment with
infliximab.
Our second microarray candidate, M-CSF, is a completely unexpected one. M-CSF has never been reported in
SpA patients. A very small number of reports suggest that
its level is increased in the serum and synovial fluids of
RA patients (16). We discovered that in the 41 AS patients
from Beijing, serum levels of M-CSF correlate both with
BASDAI and ESR. However, in the Canadian patients, they
are not significantly suppressed by infliximab treatment,
which would suggest that the M-CSF and MMP-3 constitute independent parameters.
Our discoveries regarding MMP-3 and M-CSF are also
helpful for research on the pathogenesis of SpA. The molecular pathway mediating the spondylarthropathies is unknown. Even the particular cell type that is responsible is
controversial. The once-favorite hypothesis, that the spondylarthropathies are mediated by a CD8⫹ T cell reactivity
toward self peptides, has been challenged by multiple
findings both in human subjects and in animal models (1).
One of the alternate hypotheses, for example, is that the
spondylarthropathies are induced by an endoplasmic reticulum (ER) overloading response secondary to the slow
rate of folding of the HLA–B27 heavy chains (17). What is
clear is that to induce this ER response, there must be
factors in addition to the expression of HLA–B27, and that
most likely these factors target only certain cell types, and
are localized only at the disease areas. Our preliminary
698
Yang et al
imab infusions would place the expression of M-CSF in
events upstream of those targeted by anti-TNF agents. The
decrease in MMP-3 by infliximab would place its expression downstream of those events. It is possible, for example, that the suppression of MMP-3 is secondary to the
suppression of IL-1 expression by infliximab.
The reason these 2 factors have not been subjects of SpA
research in the past is probably that their serum levels in
SpA patients are within the range of healthy subjects.
There are several possibilities why the serum levels of
MMP-3 and M-CSF in AS are within the range of healthy
subjects, and yet still correlate with disease activity.
MMP-3 can exist in at least 3 forms: pro-MMP-3, active
MMP3, and MMP-3 complexed with TIMP (10). The
ELISA method used here measures the total of all 3 forms.
It is possible that differences between AS patients and
healthy subjects can be detected if we measure these 3
forms separately. M-CSF can also exist in several forms
(20). Measurements of each of these might differentiate
between healthy subjects and AS patients. Lastly, even if
the MMP-3 and M-CSF levels in AS are in the same range
of healthy subjects, it is not a deterrent for using them in
clinical practice. Serum CRP levels in apparently healthy
individuals, for example, are frequently measured as a
predictor of heart disease (21). In the case of MMP-3, it is
not a deterrent to using it to monitor response to infliximab, provided that serum samples are obtained prior to
therapy. To assess whether measurement of MMP-3 and
M-CSF are useful in AS patients unrelated to anti-TNF
agents, we have used the multiple regression and the logistic regression analyses to test whether they account for
the variability of the BASDAI values. The results do show
a certain degree of relationship. Although BASDAI is the
current standard for evaluation of disease activity, additional assistance by objective parameters, such as those
described here, might lead to a higher degree of accuracy.
This will of course require validation.
In summary, the results of our experiments have highlighted the potential roles of MMP-3 in particular in measuring disease activity, and also both MMP-3 and M-CSF
as foci of research on disease mechanisms.
Figure 5. Effect of infliximab infusions on A, Bath Ankylosing
Disease Activity Index (BASDAI), B, serum levels of matrix metalloproteinase 3 (MMP-3), and C, macrophage colony-stimulating
factor (M-CSF). Total of 13 ankylosing spondylitis patients were
studied.
experiments have suggested that synovial monocytes/macrophages are targets of this overloading response (18).
However, no additional factors contributing to this overloading response have yet been proposed. M-CSF is
unique among potentially arthritis-causing factors in that
it affects only cells of the monocyte lineage. It can induce
replication of such cells and activate the monocytes to
contribute to inflammatory processes. Experimental animals that are deficient in M-CSF are resistant to development of collagen-induced arthritis (19). With our observation of its possible high expression in the synovial tissues,
and the positive correlation of serum levels with disease
activity, it will be useful to examine its role in the SpA
processes. The observation that it is not affected by inflix-
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