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C.-H. Chen, K.-C. Lin, D. T. Y. Yu, C. Yang, F. Huang, H.-A. Chen, T.-H. Liang, H.-T. Liao, C.-Y. Tsai, J. C. C. Wei, C.-T. Chou, Serum matrix metalloproteinases and tissue inhibitors of metalloproteinases in ankylosing spondylitis: MMP-3 is a reproducibly sensitive and specific biomarker of disease activity, Rheumatology, Volume 45, Issue 4, April 2006, Pages 414–420, https://doi.org/10.1093/rheumatology/kei208
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Abstract
Objective. To submit serum levels of matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) to statistical analyses to test their exact degrees of clinical usefulness as biomarkers for detecting high disease activity in ankylosing spondylitis (AS), comparing them with erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP).
Methods. Serum levels of MMP-1, -3, -9 and TIMP-1 and -2 were measured in 42 AS patients and 20 healthy controls. The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) provided the gold standard for measuring disease activity. Patients with BASDAI ≥4 were regarded as having high disease activity. The results were compared with results for a separate cohort of 41 AS patients.
Results. Only MMP-3 levels were significantly higher in AS patients than in healthy controls (P<0.001). Within AS patients, MMP-3 levels were also higher in patients with high disease activity compared with those with low disease activity, and correlated significantly with BASDAI (r = 0.366, P = 0.017) and functional indices (r = 0.344, P = 0.026). The correlation with BASDAI was stable in a 1-yr follow-up (r = 0.464, P = 0.095) and reproducible with two different enzyme-linked immunosorbent assays. For detecting high disease activity, the sensitivity and specificity of MMP-3 level was 69.2 and 68.8% respectively. Most importantly, using receiver operating characteristic plots to analyse the two cohorts, MMP-3 was more accurate than ESR and CRP in detecting AS patients with high disease activity (P = 0.01 and P = 0.009, respectively).
Conclusion. Using several analytical approaches that have never been reported previously, we showed that MMP-3 is a more useful biomarker than ESR and CRP to detect high disease activity in AS.
Ankylosing spondylitis (AS) is a chronic inflammatory arthritis characterized by three major musculoskeletal features: axial inflammation, peripheral arthritis and enthesitis. Degradation of the extracellular matrix (ECM) components is the pathological feature of chronic arthritis. Previous investigations have shown that matrix metalloproteinases (MMPs) play an important role in the degradation and remodelling of the ECM [1–4]. MMPs are zinc-dependent endopeptidases, essential in normal biological functions, and participate in many pathological conditions [1, 5]. MMPs are produced by fibroblasts, macrophages [6], synovial cells [7–9], endothelial cells, neutrophils and chondrocytes [10, 11] in response to proinflammatory cytokines such as interleukin-1 and tumour necrosis factor-α (TNF-α) [12, 13]. Of the MMP family, MMP-1 (interstitial collagenase 1) is important in the degradation of articular cartilage. MMP-3 (stromelysin 1) hydrolyses a number of ECM components, including aggrecan, fibronectin, laminin and collagens [14, 15] and also activates several pro-MMPs, such as pro-MMP-1 and pro-MMP-9 [5, 16]. MMP-9 (gelatinase B) digests gelatin and several types of collagens [17]. The activity of MMPs is dependent on the activation of the pro-enzymes and is regulated by specific inhibitors, such as α2-macroglobulins and tissue inhibitors of metalloproteinases (TIMPs) [5]. TIMPs inhibit MMPs by forming a 1:1 molar ratio and non-covalent complexes, blocking the access of substrates to MMPs [5]. Disruption of the balance between these proteinases and their inhibitors can lead to proteolysis in the inflamed joints [2–4].
A review of peer-reviewed full-length articles yielded only one paper published recently showing that serum MMP-3 levels correlated with the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) value in AS patients and were elevated in those with severely active disease [18]. The authors measured the serum levels of MMP-3 in a single cross-section of AS patients using one particular commercial enzyme-linked immunosorbent assay (ELISA) kit, and estimated the degree of correlation of the serum MMP-3 levels with BASDAI. If the correlation coefficient were sufficiently high and the P value low, it would be concluded that serum MMP-3 levels constitute a biomarker for AS disease activity. Although statistical correlation with BASDAI would indicate that a certain laboratory test is a promising biomarker, more analyses would be required to estimate the actual clinical usefulness of the test. These parameters would include at the minimum testing with more than one source of ELISA kit, follow-up testing of some of the patients, and, more importantly, estimation of the sensitivity, specificity, and positive and negative predictive values of the test. In addition, since erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) are existing biomarkers for AS, any new test would have to be compared with these two biomarkers using standard receiver operating characteristic (ROC) plots. Lastly, and most importantly, there should be comparison of two different cohorts derived from two different geographical sites. This is partly because BASDAI is totally dependent on subjective assessment by the patients, and might vary considerably among patient populations as well as physician populations. As far as we know, none of the previously published papers have submitted their MMP-3 data on AS to these types of challenge.
Although measurements of ESR and CRP are the most widely used methods for evaluating AS, these acute-phase reactants have not been shown to be valid indicators of disease activity in AS [19, 20]. In this study, we measured three kinds of MMP (MMP-1, -3 and -9) and their inhibitors (TIMP-1 and -2) to explore whether these biomarkers might be useful tools for assessing disease activity more accurately in AS.
Patients and methods
Patients
This research was approved by the ethical committee of Veterans General Hospital, Taipei. Before study, informed consent was obtained from all the participants. Blood samples were obtained from 42 Chinese AS patients who fulfilled the 1984 modified New York criteria [21] and visited the Outpatient Department of the Division of Allergy-Immunology-Rheumatology, Veterans General Hospital, Taipei. As a control group, blood samples from 20 age-matched Chinese healthy controls (10 men and 10 women) were also obtained. Clinical and laboratory assessments were performed on the same day. We evaluated disease activity in AS patients by using the BASDAI [22] and assessed functional ability by using the Bath Ankylosing Spondylitis Functional Index (BASFI) [23] with a visual analogue scale. The final BASDAI or BASFI scores ranged from 0 to 10. Acute-phase reactants (ESR and CRP) and immunoglobulin A (IgA) levels were also measured in these AS patients. Table 1 shows the demographic and clinical characteristics of the 42 AS patients. Furthermore, to assess the serum MMP levels longitudinally, follow-up measurements were obtained from 14 of the 42 patients.
Characteristic . | AS patients (n = 42) . |
---|---|
Age (yr) | 36.6 (12.0) |
Male/female | 34/8 |
Disease duration (yr) | 12 (10) |
Peripheral arthritis/axial disease only | 22/20 |
BASDAI | 4.31 (2.09) |
BASFI | 3.36 (2.89) |
CRP (mg/dl) | 1.66 (1.67) |
ESR (mm/h) | 29.8 (31.54) |
IgA (mg/dl) | 305.1 (125.6) |
Medication: no. taking/not taking | |
NSAID | 25/17 |
DMARD | 12/30 |
Characteristic . | AS patients (n = 42) . |
---|---|
Age (yr) | 36.6 (12.0) |
Male/female | 34/8 |
Disease duration (yr) | 12 (10) |
Peripheral arthritis/axial disease only | 22/20 |
BASDAI | 4.31 (2.09) |
BASFI | 3.36 (2.89) |
CRP (mg/dl) | 1.66 (1.67) |
ESR (mm/h) | 29.8 (31.54) |
IgA (mg/dl) | 305.1 (125.6) |
Medication: no. taking/not taking | |
NSAID | 25/17 |
DMARD | 12/30 |
Values are mean (s.d.).
Characteristic . | AS patients (n = 42) . |
---|---|
Age (yr) | 36.6 (12.0) |
Male/female | 34/8 |
Disease duration (yr) | 12 (10) |
Peripheral arthritis/axial disease only | 22/20 |
BASDAI | 4.31 (2.09) |
BASFI | 3.36 (2.89) |
CRP (mg/dl) | 1.66 (1.67) |
ESR (mm/h) | 29.8 (31.54) |
IgA (mg/dl) | 305.1 (125.6) |
Medication: no. taking/not taking | |
NSAID | 25/17 |
DMARD | 12/30 |
Characteristic . | AS patients (n = 42) . |
---|---|
Age (yr) | 36.6 (12.0) |
Male/female | 34/8 |
Disease duration (yr) | 12 (10) |
Peripheral arthritis/axial disease only | 22/20 |
BASDAI | 4.31 (2.09) |
BASFI | 3.36 (2.89) |
CRP (mg/dl) | 1.66 (1.67) |
ESR (mm/h) | 29.8 (31.54) |
IgA (mg/dl) | 305.1 (125.6) |
Medication: no. taking/not taking | |
NSAID | 25/17 |
DMARD | 12/30 |
Values are mean (s.d.).
Finally, to compare the performance of each biomarker in a completely different cohort, data from 41 AS patients in Beijing were also analysed [18]. The degree of correlation between MMP-3 and BASDAI in this cohort has been published previously. The clinical data were collected and laboratory tests were carried out for the Taipei and Beijing cohorts by two completely different groups of investigators in two completely different facilities. The translations of the BASDAI questionnaire for the two cohorts were not identical. The Mandarin version of BASDAI used in Taipei has been validated at Chung Shan Medical University, Taichung, and its usefulness in monitoring response to treatment in Taiwan has been reported [24]. Likewise, the BASDAI used in Beijing has also been validated and the usefulness was confirmed by its effectiveness in monitoring patients with therapy [25].
Serum sample preparation
Samples of peripheral blood were allowed to clot and were then centrifuged at 2400 g for 10 min. The sera were frozen at −80°C immediately after sample collection.
Immunoassays of biomarkers
Serum concentrations of MMP-1, -3 and -9 and TIMP-1 and -2 were measured with a quantitative sandwich ELISA (Quantikine; R & D Systems, USA) according to the manufacturer's instructions and carried out in duplicate. These immunoassays were designed to measure concentrations of pro-MMP-1, MMP-3 (pro- and active MMP-3), MMP-9 (pro- and active MMP-9), TIMP-1 and TIMP-2. The dilution levels for the serum samples were as follows: 1:1 for MMP-1, 1:10 for MMP-3, 1:100 for MMP-9, 1:100 for TIMP-1 and 1:50 for TIMP-2. The sensitivities were 0.021 ng/ml for MMP-1, 0.009 ng/ml for MMP-3, 0.005 ng/ml for MMP-9, 0.08 ng/ml for TIMP-1 and 0.01 ng/ml for TIMP-2.
Serum MMP-3 levels measured by another ELISA kit
To test the reproducibility of serum MMP-3 levels in various commercial kits, serum MMP-3 levels in the same samples were measured with a different commercial kit, the human MMP-3 Biotrak ELISA system (Amersham). This kit measured three forms of MMP-3, including pro-MMP-3, active MMP-3 and MMP-3/TIMPs complex. The number of healthy controls in this test was expanded to 40. The dilution level was 1:8 and the sensitivity of the assay was 2.35 ng/ml.
Statistical analysis
Statistical analyses were carried out using the SPSS statistical package. The Mann–Whitney U-test and Fisher's exact test were used, as appropriate, to analyse group differences. Correlations between variables were determined with the Spearman's rank correlation test. Bonferroni correction for multiple testing was applied where indicated. We used ROC plot analysis to evaluate and compare the performance of each biomarker. ROC analysis is a non-parametric method used to quantify the accuracy of the prediction. Two-graph ROC (TG-ROC) analysis was used to compare the whole spectrum of sensitivity and specificity of different markers and to choose an optimal cut-off value for each marker. P values were provisionally regarded as being significant if they were less than 0.05.
Results
Serum levels of MMPs and TIMPs in AS patients and healthy controls
We compared serum levels of MMP-1, -3 and -9 and TIMP-1 and -2 between the 42 AS patients and the 20 healthy controls (Table 2). Serum MMP-3 levels were significantly higher in AS patients than in healthy controls (P<0.001), and the difference remained significant when Bonferroni correction was applied. Serum levels of MMP-1, MMP-9 and TIMP-1 did not show significant differences between AS patients and healthy controls. Thirty-one per cent of the AS patients (13/42) had serum MMP-3 levels greater than the mean + 2 s.d. of healthy controls. On the other hand, serum TIMP-2 levels had a tendency to decrease in AS patients (P = 0.071). Twenty-four per cent of the AS patients (10/42) had serum TIMP-2 levels below the mean − 2 s.d. of healthy controls.
. | AS patients (n = 42) . | Healthy controls (n = 20) . | P . |
---|---|---|---|
MMP-1 | 8.63 (7.2), 7.26 (0.64–40.51) | 7.44 (3.27), 6.55 (2.02–12.9) | 0.952 |
MMP-3 | 29.77 (16.9), 26.11 (9.07–97.95) | 15.45 (10), 13.73 (5.36–45.66) | <0.001a |
MMP-9 | 653.96 (450.94), 541.74 (75.77–1983.25) | 705.34 (379.88), 623.93 (190.27–1562.8) | 0.470 |
TIMP-1 | 164.14 (34.08), 166.4 (69.70–234.5) | 172.37 (33.30), 162.5 (129–239.1) | 0.662 |
TIMP-2 | 69.04 (10.61), 70.46 (45.57–92.9) | 74.13 (6.67), 75.04 (63.2–83.18) | 0.071 |
. | AS patients (n = 42) . | Healthy controls (n = 20) . | P . |
---|---|---|---|
MMP-1 | 8.63 (7.2), 7.26 (0.64–40.51) | 7.44 (3.27), 6.55 (2.02–12.9) | 0.952 |
MMP-3 | 29.77 (16.9), 26.11 (9.07–97.95) | 15.45 (10), 13.73 (5.36–45.66) | <0.001a |
MMP-9 | 653.96 (450.94), 541.74 (75.77–1983.25) | 705.34 (379.88), 623.93 (190.27–1562.8) | 0.470 |
TIMP-1 | 164.14 (34.08), 166.4 (69.70–234.5) | 172.37 (33.30), 162.5 (129–239.1) | 0.662 |
TIMP-2 | 69.04 (10.61), 70.46 (45.57–92.9) | 74.13 (6.67), 75.04 (63.2–83.18) | 0.071 |
Values are mean (s.d.), median (range). P values were determined with the Mann–Whitney U-test. aSignificant difference with Bonferroni correction (α/m).
. | AS patients (n = 42) . | Healthy controls (n = 20) . | P . |
---|---|---|---|
MMP-1 | 8.63 (7.2), 7.26 (0.64–40.51) | 7.44 (3.27), 6.55 (2.02–12.9) | 0.952 |
MMP-3 | 29.77 (16.9), 26.11 (9.07–97.95) | 15.45 (10), 13.73 (5.36–45.66) | <0.001a |
MMP-9 | 653.96 (450.94), 541.74 (75.77–1983.25) | 705.34 (379.88), 623.93 (190.27–1562.8) | 0.470 |
TIMP-1 | 164.14 (34.08), 166.4 (69.70–234.5) | 172.37 (33.30), 162.5 (129–239.1) | 0.662 |
TIMP-2 | 69.04 (10.61), 70.46 (45.57–92.9) | 74.13 (6.67), 75.04 (63.2–83.18) | 0.071 |
. | AS patients (n = 42) . | Healthy controls (n = 20) . | P . |
---|---|---|---|
MMP-1 | 8.63 (7.2), 7.26 (0.64–40.51) | 7.44 (3.27), 6.55 (2.02–12.9) | 0.952 |
MMP-3 | 29.77 (16.9), 26.11 (9.07–97.95) | 15.45 (10), 13.73 (5.36–45.66) | <0.001a |
MMP-9 | 653.96 (450.94), 541.74 (75.77–1983.25) | 705.34 (379.88), 623.93 (190.27–1562.8) | 0.470 |
TIMP-1 | 164.14 (34.08), 166.4 (69.70–234.5) | 172.37 (33.30), 162.5 (129–239.1) | 0.662 |
TIMP-2 | 69.04 (10.61), 70.46 (45.57–92.9) | 74.13 (6.67), 75.04 (63.2–83.18) | 0.071 |
Values are mean (s.d.), median (range). P values were determined with the Mann–Whitney U-test. aSignificant difference with Bonferroni correction (α/m).
Correlations between biomarkers and clinical parameters
Correlations between different parameters in the 42 AS patients were calculated. The correlation matrix is shown in Table 3. The highest correlation coefficient observed was between ESR and CRP (r = 0.76). The second highest was between BASDAI and BASFI (r = 0.61). For BASDAI, the highest correlation was with MMP-3 (r = 0.37). Remarkably, the correlation of BASDAI with all other parameters was very poor (r<0.25), even with ESR and CRP. MMP-3 also correlated with ESR, CRP and BASFI to the same extent as with BASDAI. Although the MMP-3 levels correlated significantly with BASDAI (P = 0.017), the correlation showed a moderate degree as the Spearman correlation coefficient was 0.37.
. | MMP-3 . | MMP-9 . | TIMP-1 . | TIMP-2 . | ESR . | CRP . | BASDAI . | BASFI . |
---|---|---|---|---|---|---|---|---|
MMP-1 | −0.086 | 0.064 | 0.412 (0.007) | −0.225 | 0.323 (0.037) | 0.314 (0.043) | −0.029 | 0.16 |
MMP-3 | 0.119 | 0.362 (0.018) | 0.076 | 0.383 (0.012) | 0.416 (0.006) | 0.366 (0.017) | 0.344 (0.026) | |
MMP-9 | 0.304 | 0.129 | 0.266 | 0.258 | −0.115 | 0.11 | ||
TIMP-1 | −0.049 | 0.625 (<0.001) | 0.576 (<0.001) | 0.165 | 0.266 | |||
TIMP-2 | −0.104 | −0.216 | −0.188 | −0.047 | ||||
ESR | 0.765 (<0.001) | 0.133 | 0.376 (0.014) | |||||
CRP | 0.204 | 0.386 (0.012) | ||||||
BASDAI | 0.611 (<0.001) |
. | MMP-3 . | MMP-9 . | TIMP-1 . | TIMP-2 . | ESR . | CRP . | BASDAI . | BASFI . |
---|---|---|---|---|---|---|---|---|
MMP-1 | −0.086 | 0.064 | 0.412 (0.007) | −0.225 | 0.323 (0.037) | 0.314 (0.043) | −0.029 | 0.16 |
MMP-3 | 0.119 | 0.362 (0.018) | 0.076 | 0.383 (0.012) | 0.416 (0.006) | 0.366 (0.017) | 0.344 (0.026) | |
MMP-9 | 0.304 | 0.129 | 0.266 | 0.258 | −0.115 | 0.11 | ||
TIMP-1 | −0.049 | 0.625 (<0.001) | 0.576 (<0.001) | 0.165 | 0.266 | |||
TIMP-2 | −0.104 | −0.216 | −0.188 | −0.047 | ||||
ESR | 0.765 (<0.001) | 0.133 | 0.376 (0.014) | |||||
CRP | 0.204 | 0.386 (0.012) | ||||||
BASDAI | 0.611 (<0.001) |
Values are r (P value), determined with Spearman's rank correlation test. Values of r exceeding 0.33 are in bold type.
. | MMP-3 . | MMP-9 . | TIMP-1 . | TIMP-2 . | ESR . | CRP . | BASDAI . | BASFI . |
---|---|---|---|---|---|---|---|---|
MMP-1 | −0.086 | 0.064 | 0.412 (0.007) | −0.225 | 0.323 (0.037) | 0.314 (0.043) | −0.029 | 0.16 |
MMP-3 | 0.119 | 0.362 (0.018) | 0.076 | 0.383 (0.012) | 0.416 (0.006) | 0.366 (0.017) | 0.344 (0.026) | |
MMP-9 | 0.304 | 0.129 | 0.266 | 0.258 | −0.115 | 0.11 | ||
TIMP-1 | −0.049 | 0.625 (<0.001) | 0.576 (<0.001) | 0.165 | 0.266 | |||
TIMP-2 | −0.104 | −0.216 | −0.188 | −0.047 | ||||
ESR | 0.765 (<0.001) | 0.133 | 0.376 (0.014) | |||||
CRP | 0.204 | 0.386 (0.012) | ||||||
BASDAI | 0.611 (<0.001) |
. | MMP-3 . | MMP-9 . | TIMP-1 . | TIMP-2 . | ESR . | CRP . | BASDAI . | BASFI . |
---|---|---|---|---|---|---|---|---|
MMP-1 | −0.086 | 0.064 | 0.412 (0.007) | −0.225 | 0.323 (0.037) | 0.314 (0.043) | −0.029 | 0.16 |
MMP-3 | 0.119 | 0.362 (0.018) | 0.076 | 0.383 (0.012) | 0.416 (0.006) | 0.366 (0.017) | 0.344 (0.026) | |
MMP-9 | 0.304 | 0.129 | 0.266 | 0.258 | −0.115 | 0.11 | ||
TIMP-1 | −0.049 | 0.625 (<0.001) | 0.576 (<0.001) | 0.165 | 0.266 | |||
TIMP-2 | −0.104 | −0.216 | −0.188 | −0.047 | ||||
ESR | 0.765 (<0.001) | 0.133 | 0.376 (0.014) | |||||
CRP | 0.204 | 0.386 (0.012) | ||||||
BASDAI | 0.611 (<0.001) |
Values are r (P value), determined with Spearman's rank correlation test. Values of r exceeding 0.33 are in bold type.
Serum levels of MMPs and TIMPs in AS patients with BASDAI <4 and ≥4
Next, we divided the AS patents into two subgroups, those with BASDAI <4 and those with BASDAI ≥4. These were arbitrarily defined as AS patients with low and high disease activity. The numbers of AS patients in these two subgroups were 16 and 26 respectively. Serum levels of MMP-1, -3 and -9 and TIMP-1 and -2 were compared between these two subgroups. In addition, the differences in acute-phase reactants (ESR and CRP) and IgA level between these two groups were also analysed. As shown in Table 4, serum MMP-3 levels were significantly higher in AS patients with high disease activity than in those with low disease activity (P = 0.01), and the difference remained significant if Bonferroni correction was done. Serum levels of MMP-1, MMP-9, TIMP-1 and TIMP-2 revealed no significant differences between these two subgroups. Although ESR and CRP level in AS patients with high disease activity were elevated compared with those with low disease activity, the differences were statistically insignificant.
. | BASDAI <4 (n = 16) (A) . | BASDAI ≥4 (n = 26) (B) . | P (A vs B) . | P (A vs controls) . | P (B vs controls) . |
---|---|---|---|---|---|
MMP-1 (ng/ml) | 8.4 (5.89), 7.59 (0.62–24.94) | 8.78 (8.01), 6.86 (1.23–40.51) | 0.660 | 0.750 | 0.894 |
MMP-3 (ng/ml) | 22.34 (11.5), 20.33 (9.07–55.5) | 34.34 (18.21), 31.1 (1.33–97.95) | 0.01a | 0.024 | <0.001a |
MMP-9 (ng/ml) | 683.59 (479.2), 537.91 (75.77–1983.25) | 635.72 (429.25), 541.74 (147.84–1851.35) | 0.836 | 0.656 | 0.458 |
TIMP-1 (ng/ml) | 156.11(38), 164.25 (69.7–198.3) | 169.08 (31.16), 176.5 (108.1–234.5) | 0.468 | 0.340 | 0.982 |
TIMP-2 (ng/ml) | 69.3 (12.72), 74.02 (45.57–86.76) | 68.88 (9.35), 69.312 (53.53–92.9) | 0.325 | 0.417 | 0.037 |
ESR (mm/h) | 18.63 (16.98), 13 (1–60) | 36.77 (36.44), 27 (0–132) | 0.228 | – | – |
CRP (mg/dl) | 1.23 (1.33), 0.69 (0.3–4.71) | 1.86 (1.91), 1.55 (0.3–6.73) | 0.15 | – | – |
IgA (mg/dl) | 286.06 (77.12), 295 (141–428) | 316.85 (148.11), 265 (94.2–604) | 0.907 | – | – |
Disease duration (yr) | 12.25 (12.39), 7 (1–45) | 11.58 (8.55), 8.5 (1–30) | 0.516 | – | – |
Peripheral arthritis | 3/16 (19%) | 19/26 (73%) | 0.001b | – | – |
. | BASDAI <4 (n = 16) (A) . | BASDAI ≥4 (n = 26) (B) . | P (A vs B) . | P (A vs controls) . | P (B vs controls) . |
---|---|---|---|---|---|
MMP-1 (ng/ml) | 8.4 (5.89), 7.59 (0.62–24.94) | 8.78 (8.01), 6.86 (1.23–40.51) | 0.660 | 0.750 | 0.894 |
MMP-3 (ng/ml) | 22.34 (11.5), 20.33 (9.07–55.5) | 34.34 (18.21), 31.1 (1.33–97.95) | 0.01a | 0.024 | <0.001a |
MMP-9 (ng/ml) | 683.59 (479.2), 537.91 (75.77–1983.25) | 635.72 (429.25), 541.74 (147.84–1851.35) | 0.836 | 0.656 | 0.458 |
TIMP-1 (ng/ml) | 156.11(38), 164.25 (69.7–198.3) | 169.08 (31.16), 176.5 (108.1–234.5) | 0.468 | 0.340 | 0.982 |
TIMP-2 (ng/ml) | 69.3 (12.72), 74.02 (45.57–86.76) | 68.88 (9.35), 69.312 (53.53–92.9) | 0.325 | 0.417 | 0.037 |
ESR (mm/h) | 18.63 (16.98), 13 (1–60) | 36.77 (36.44), 27 (0–132) | 0.228 | – | – |
CRP (mg/dl) | 1.23 (1.33), 0.69 (0.3–4.71) | 1.86 (1.91), 1.55 (0.3–6.73) | 0.15 | – | – |
IgA (mg/dl) | 286.06 (77.12), 295 (141–428) | 316.85 (148.11), 265 (94.2–604) | 0.907 | – | – |
Disease duration (yr) | 12.25 (12.39), 7 (1–45) | 11.58 (8.55), 8.5 (1–30) | 0.516 | – | – |
Peripheral arthritis | 3/16 (19%) | 19/26 (73%) | 0.001b | – | – |
Values are mean (s.d.), median (range). P values were determined with the Mann–Whitney U-test. aSignificant difference with Bonferroni correction (α/m). bP value calculated with Fisher's exact test.
. | BASDAI <4 (n = 16) (A) . | BASDAI ≥4 (n = 26) (B) . | P (A vs B) . | P (A vs controls) . | P (B vs controls) . |
---|---|---|---|---|---|
MMP-1 (ng/ml) | 8.4 (5.89), 7.59 (0.62–24.94) | 8.78 (8.01), 6.86 (1.23–40.51) | 0.660 | 0.750 | 0.894 |
MMP-3 (ng/ml) | 22.34 (11.5), 20.33 (9.07–55.5) | 34.34 (18.21), 31.1 (1.33–97.95) | 0.01a | 0.024 | <0.001a |
MMP-9 (ng/ml) | 683.59 (479.2), 537.91 (75.77–1983.25) | 635.72 (429.25), 541.74 (147.84–1851.35) | 0.836 | 0.656 | 0.458 |
TIMP-1 (ng/ml) | 156.11(38), 164.25 (69.7–198.3) | 169.08 (31.16), 176.5 (108.1–234.5) | 0.468 | 0.340 | 0.982 |
TIMP-2 (ng/ml) | 69.3 (12.72), 74.02 (45.57–86.76) | 68.88 (9.35), 69.312 (53.53–92.9) | 0.325 | 0.417 | 0.037 |
ESR (mm/h) | 18.63 (16.98), 13 (1–60) | 36.77 (36.44), 27 (0–132) | 0.228 | – | – |
CRP (mg/dl) | 1.23 (1.33), 0.69 (0.3–4.71) | 1.86 (1.91), 1.55 (0.3–6.73) | 0.15 | – | – |
IgA (mg/dl) | 286.06 (77.12), 295 (141–428) | 316.85 (148.11), 265 (94.2–604) | 0.907 | – | – |
Disease duration (yr) | 12.25 (12.39), 7 (1–45) | 11.58 (8.55), 8.5 (1–30) | 0.516 | – | – |
Peripheral arthritis | 3/16 (19%) | 19/26 (73%) | 0.001b | – | – |
. | BASDAI <4 (n = 16) (A) . | BASDAI ≥4 (n = 26) (B) . | P (A vs B) . | P (A vs controls) . | P (B vs controls) . |
---|---|---|---|---|---|
MMP-1 (ng/ml) | 8.4 (5.89), 7.59 (0.62–24.94) | 8.78 (8.01), 6.86 (1.23–40.51) | 0.660 | 0.750 | 0.894 |
MMP-3 (ng/ml) | 22.34 (11.5), 20.33 (9.07–55.5) | 34.34 (18.21), 31.1 (1.33–97.95) | 0.01a | 0.024 | <0.001a |
MMP-9 (ng/ml) | 683.59 (479.2), 537.91 (75.77–1983.25) | 635.72 (429.25), 541.74 (147.84–1851.35) | 0.836 | 0.656 | 0.458 |
TIMP-1 (ng/ml) | 156.11(38), 164.25 (69.7–198.3) | 169.08 (31.16), 176.5 (108.1–234.5) | 0.468 | 0.340 | 0.982 |
TIMP-2 (ng/ml) | 69.3 (12.72), 74.02 (45.57–86.76) | 68.88 (9.35), 69.312 (53.53–92.9) | 0.325 | 0.417 | 0.037 |
ESR (mm/h) | 18.63 (16.98), 13 (1–60) | 36.77 (36.44), 27 (0–132) | 0.228 | – | – |
CRP (mg/dl) | 1.23 (1.33), 0.69 (0.3–4.71) | 1.86 (1.91), 1.55 (0.3–6.73) | 0.15 | – | – |
IgA (mg/dl) | 286.06 (77.12), 295 (141–428) | 316.85 (148.11), 265 (94.2–604) | 0.907 | – | – |
Disease duration (yr) | 12.25 (12.39), 7 (1–45) | 11.58 (8.55), 8.5 (1–30) | 0.516 | – | – |
Peripheral arthritis | 3/16 (19%) | 19/26 (73%) | 0.001b | – | – |
Values are mean (s.d.), median (range). P values were determined with the Mann–Whitney U-test. aSignificant difference with Bonferroni correction (α/m). bP value calculated with Fisher's exact test.
In addition, we compared the high and low disease activity subgroups separately with the values observed in healthy controls. Serum MMP-3 levels in each subgroup were significantly higher than in healthy controls (P = 0.024 and P<0.001, respectively). In contrast, serum TIMP-2 levels in the AS subgroup with high disease activity were significantly lower than in healthy controls (P = 0.037). With Bonferroni correction, the only statistically significant value observed was the difference in MMP-3 between the group with high disease activity and healthy controls.
Noticeably, the occurrence of peripheral arthritis was significantly higher in AS patients with BASDAI ≥4 than in those with BASDAI <4 (P = 0.001) (Table 4). Peripheral arthritis was defined as at least one swollen peripheral joint observed. Serum MMP-3 levels were significantly higher in AS patients with peripheral arthritis than in those with axial disease only [mean (s.d.), 36.22 (19.99) vs 22.68 (8.57) ng/ml; P = 0.013].
Concentration ratio of MMPs to TIMPs
Because connective tissue turnover occurs as a result of excessive MMP over TIMP activity, concentration ratios of MMPs/TIMPs were calculated. Concentration ratios of MMP-3/TIMP-1 and MMP-3/TIMP-2 were significantly higher in AS patients than in healthy controls (P<0.001 and P<0.001, respectively) and the difference remained significant when Bonferroni correction was applied. Nevertheless, such differences were not evident in concentration ratios of MMP-1/TIMP-1, MMP-1/TIMP-2, MMP-9/TIMP-1 and MMP-9/TIMP-2 (data not shown).
Of the six ratios calculated for MMPs/TIMPs, only the MMP-3/TIMP-2 ratio was higher in the AS subgroup with BASDAI ≥4 than in those with BASDAI <4 (P = 0.01). However, this difference did not remain significant after Bonferroni correction. In addition, this ratio (MMP-3/TIMP-2) correlated significantly with BASDAI (r = 0.392, P = 0.01).
Longitudinal follow-up
Finally, to determine whether serum MMP-3 levels correlated with disease activity longitudinally, 14 of the 42 AS patients were available for a follow-up study. The duration [median (range)] of follow-up in these 14 patients was 12 (5–18) months. The correlation coefficient between change in MMP-3 and change in BASDAI was still high (0.464), but because of the small sample size the P value was only 0.095 (Fig. 1). Change in MMP-3 and BASDAI was defined as the difference between the initial and follow-up measurements.
Reproducibility of interpretation when serum MMP-3 levels were measured with another ELISA kit
Serum MMP-3 levels measured with another kit (Amersham) were also significantly higher in the 42 AS patients than in the 40 healthy controls [mean (s.d.), 80.99 (62.55) vs 53.06 (32.63) ng/ml; P = 0.006]. Serum MMP-3 levels also correlated significantly with BASDAI (r = 0.313, P = 0.044). Both these results were consistent with the findings obtained by using the R & D Systems kit, although the serum concentrations of MMP-3 measured by the two kits were different. The mean (s.d.) serum MMP-3 levels measured by the R & D Systems kit were 29.77 (16.9) ng/ml. In addition, serum MMP-3 levels obtained with the Amersham kit were significantly correlated with those obtained with the R & D Systems kit (r = 0.75, P<0.001) (Fig. 2).
Statistical evaluation of the potential usefulness of MMP-3 as a biomarker for detecting AS patients with high disease activity
To evaluate with statistical tools the degree of usefulness of ESR, CRP and MMP-3 in detecting patients with BASDAI ≥4, a threshold cut-off value for each of these measurements was selected by using TG-ROC analysis. Patients with BASDAI ≥4 are conventionally considered as having sufficiently high BASDAI to warrant TNF blocker treatment [26]. As in all clinical laboratory tests, values higher than the cut-off would be regarded as being positive rather than negative. For ESR, CRP and MMP-3, the cut-off values selected were ≥18.7 mm/h, ≥1.0 mg/dl and ≥24.4 ng/ml respectively. Using the above thresholds, the usefulnesses of the three biomarkers are as follows: ESR, sensitivity 61.5%, specificity 62.5%, positive predictive value (PPV) 72.7%, and negative predictive value (NPV) 50%; CRP, sensitivity 61.5%, specificity 62.5%, PPV 72.7% and NPV 50%; MMP-3, sensitivity 69.2%, specificity 68.8%, PPV 78.3% and NPV 57.9%. The accuracies of ESR and CRP were quite similar. When the specificity of MMP-3 was adjusted to a level similar to ESR and CRP at 62.5%, the sensitivity of MMP-3 reached 73.1%. If a positive MMP-3 level was defined as equal to or greater than the mean + 2 s.d. for healthy controls, there were improvements in specificity (87.5%) and PPV (84.6%) at the cost of sensitivity (42.3%) and NPV (48.3%).
To compare the usefulness of the three biomarkers using a statistical tool which could generate a P value, we calculated the area under the curve (AUC) at each BASDAI cut-off using ROC plots. The best AUC is when MMP-3 discriminates patients with BASDAI <3 from those with BASDAI ≥3 (AUC value 0.77). ESR and CRP were best in discriminating patients with BASDAI <4 from those with BASDAI ≥4. However, the AUC values for these comparisons were only 0.61 and 0.63, respectively. When the AUC values for MMP-3 were compared with those for ESR and CRP, the values were statistically higher for MMP-3 at BASDAI cut-offs of ≥2, ≥3 and ≥4 (Table 5). The entire ROC plot for BASDAI ≥4 is shown in Fig. 3A.
. | BASDAI cut-off points . | . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|---|
. | ≥2 . | ≥3 . | ≥4 . | ≥5 . | ≥6 . | ||||
Taipei cohort | |||||||||
ESR | 0.572 (0.532) | 0.599 (0.308) | 0.612 (0.228) | 0.525 (0.788) | 0.583 (0.434) | ||||
CRP | 0.583 (0.471) | 0.605 (0.283) | 0.631 (0.158) | 0.578 (0.398) | 0.517 (0.871) | ||||
MMP-3 | 0.743 (0.035)a | 0.772 (0.005)a | 0.74 (0.01)a | 0.624 (0.179) | 0.6 (0.345) | ||||
Beijing cohort | |||||||||
ESR | – | – | 0.635 (0.245) | 0.668 (0.081) | 0.692 (0.051) | ||||
CRP | – | – | 0.594 (0.42) | 0.645 (0.132) | 0.54 (0.683) | ||||
MMP-3 | – | – | 0.719 (0.06) | 0.75 (0.009)a | 0.743 (0.014)a |
. | BASDAI cut-off points . | . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|---|
. | ≥2 . | ≥3 . | ≥4 . | ≥5 . | ≥6 . | ||||
Taipei cohort | |||||||||
ESR | 0.572 (0.532) | 0.599 (0.308) | 0.612 (0.228) | 0.525 (0.788) | 0.583 (0.434) | ||||
CRP | 0.583 (0.471) | 0.605 (0.283) | 0.631 (0.158) | 0.578 (0.398) | 0.517 (0.871) | ||||
MMP-3 | 0.743 (0.035)a | 0.772 (0.005)a | 0.74 (0.01)a | 0.624 (0.179) | 0.6 (0.345) | ||||
Beijing cohort | |||||||||
ESR | – | – | 0.635 (0.245) | 0.668 (0.081) | 0.692 (0.051) | ||||
CRP | – | – | 0.594 (0.42) | 0.645 (0.132) | 0.54 (0.683) | ||||
MMP-3 | – | – | 0.719 (0.06) | 0.75 (0.009)a | 0.743 (0.014)a |
Values are area (P value). aStatistically significant. Null hypothesis: true area = 0.5.
. | BASDAI cut-off points . | . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|---|
. | ≥2 . | ≥3 . | ≥4 . | ≥5 . | ≥6 . | ||||
Taipei cohort | |||||||||
ESR | 0.572 (0.532) | 0.599 (0.308) | 0.612 (0.228) | 0.525 (0.788) | 0.583 (0.434) | ||||
CRP | 0.583 (0.471) | 0.605 (0.283) | 0.631 (0.158) | 0.578 (0.398) | 0.517 (0.871) | ||||
MMP-3 | 0.743 (0.035)a | 0.772 (0.005)a | 0.74 (0.01)a | 0.624 (0.179) | 0.6 (0.345) | ||||
Beijing cohort | |||||||||
ESR | – | – | 0.635 (0.245) | 0.668 (0.081) | 0.692 (0.051) | ||||
CRP | – | – | 0.594 (0.42) | 0.645 (0.132) | 0.54 (0.683) | ||||
MMP-3 | – | – | 0.719 (0.06) | 0.75 (0.009)a | 0.743 (0.014)a |
. | BASDAI cut-off points . | . | . | . | . | ||||
---|---|---|---|---|---|---|---|---|---|
. | ≥2 . | ≥3 . | ≥4 . | ≥5 . | ≥6 . | ||||
Taipei cohort | |||||||||
ESR | 0.572 (0.532) | 0.599 (0.308) | 0.612 (0.228) | 0.525 (0.788) | 0.583 (0.434) | ||||
CRP | 0.583 (0.471) | 0.605 (0.283) | 0.631 (0.158) | 0.578 (0.398) | 0.517 (0.871) | ||||
MMP-3 | 0.743 (0.035)a | 0.772 (0.005)a | 0.74 (0.01)a | 0.624 (0.179) | 0.6 (0.345) | ||||
Beijing cohort | |||||||||
ESR | – | – | 0.635 (0.245) | 0.668 (0.081) | 0.692 (0.051) | ||||
CRP | – | – | 0.594 (0.42) | 0.645 (0.132) | 0.54 (0.683) | ||||
MMP-3 | – | – | 0.719 (0.06) | 0.75 (0.009)a | 0.743 (0.014)a |
Values are area (P value). aStatistically significant. Null hypothesis: true area = 0.5.
Serum MMP-3, ESR and CRP in the Beijing cohort
We again used the ROC plot to compare the performance of these three biomarkers in the 41 AS patients of the Beijing cohort. Except for the ROC analyses, details of this cohort have been reported previously [18]. In this Beijing cohort, the mean MMP-3 level of AS patients, measured with the human MMP-3 Biotrak ELISA system (Amersham), was not higher than that of healthy subjects. Hence, in our analysis we used the median MMP-3 level as the threshold to distinguish between high and low MMP-3 values. Because this Beijing cohort was skewed towards patients with high BASDAI values, comparisons were made at cut-offs of BASDAI ≥4, ≥5 and ≥6. Remarkably, the AUC values were high (0.72–0.75) at BASDAI cut-offs of ≥4, ≥5 and ≥6. The AUC for MMP-3 was statistically higher than corresponding values for ESR and CRP (Table 5). An ROC plot with a BASDAI cut-off at ≥5 is shown in Fig. 3B.
Discussion
Our data showed that serum MMP-3 levels were significantly higher in AS patients than in healthy individuals, and to an even greater extent in patients with high disease activity (BASDAI ≥4). In addition, serum MMP-3 levels closely correlated with disease activity in cross-sectional and longitudinal analyses. These results indicate that serum MMP-3 is a promising marker for assessing AS disease activity. Besides digesting components of ECM, MMP-3 activates a number of pro-MMPs and is critical in the full generation of active MMPs [5, 16]. It plays a key role in cartilage damage and joint destruction. Serum MMP-3, originating directly from the inflamed joints, could be a specific marker of active inflammation inside the joints [27].
Of the three MMPs and two TIMPs studied, MMP-3 had a significantly higher serum level in AS patients than in healthy individuals. Moreover, a significant increase in serum MMP-3 level was observed in patients with high disease activity. Thus, elevation of serum MMP-3 levels is closely associated with the disease process in AS. While Ribbens et al. reported only 11% (1/9) of AS patients had abnormal serum MMP-3 levels, 31% (13/42) of our patients had abnormal serum MMP-3 levels using the same criterion (above the mean + 2 s.d. of healthy controls) [28]. Yang et al. [18] also showed no significant difference in serum MMP-3 levels between 41 AS patients and 28 healthy individuals in the Beijing cohort. These differences in findings may be due to the analysis kits used, which measured different MMP-3 components. In these two studies, by Ribbens and Yang, all three components of MMP-3 (pro-MMP-3, active MMP-3 and MMP-3/TIMPs complex) were measured vs two components (pro-MMP-3 and active MMP-3) in our test. The additional measurement of MMP-3/TIMPs complex was probably the cause of the different results among these studies. Therefore, it is reasonable to believe that active MMP-3 levels may truly dictate MMP-3 activity. More importantly, the balance between MMPs and TIMPs is a determinant of whether MMPs degrade the components of ECM and cause joint damage. Our data further emphasize this concept, as higher concentration ratios of MMP-3/TIMP-1 and MMP-3/TIMP-2 were revealed in AS patients compared with healthy individuals.
Serum MMP-3 levels correlated significantly with disease activity (BASDAI), functional ability (BASFI) and acute-phase reactants (ESR and CRP level) in our study. Furthermore, in the 14 follow-ups of the 42 AS patients, change in MMP-3 showed a close correlation with change in BASDAI. Yang's study in the Beijing cohort showed the same result—that serum MMP-3 levels correlated with BASDAI and ESR [18]. Recently, with the advance in the treatment of AS with TNF blockers [29, 30], it is imperative to evaluate disease activity and monitor therapeutic efficacy more accurately. Yang et al. [18] showed that both serum MMP-3 levels and BASDAI decreased significantly after infliximab infusion. Maksymowych et al. [31] also observed a significant correlation between change in BASDAI and change in serum MMP-3 levels in AS patients with 14 weeks of infliximab therapy. A similar observation was made in RA, where serum MMP-3 levels correlated with disease activity scores, CRP and IL-6 serum levels [32]. As in other studies, serum MMP-3 can also predict the progression of joint damage in early RA [33, 34]. Taken together, serum MMP-3 could be of value in assessing AS disease activity both cross-sectionally and longitudinally, and acts as an indicator of response to biological therapies.
ESR and CRP are the commonly used biomarkers for disease activity in AS. Nonetheless, correlations between BASDAI and acute-phase reactants (ESR and CRP level) were not observed in our data. Moreover, although ESR and CRP level were elevated in AS patients with high disease activity compared with those with low disease activity, the differences were statistically not significant. This would indicate that, at least in this particular cohort, disease activity in AS patients was not well reflected by ESR and CRP level. Consistent with previous studies, ESR and CRP cannot be used as the only parameters for evaluating AS disease activity [19, 20]. Actually, there is no standard method to assess disease activity in AS patients at present. Physicians and patients may judge the disease activity on different bases [35]. In this study, BASDAI was provisionally regarded as the gold standard. It was recently observed that the ratio of serum C-propeptide of type II collagen (CPII) to Col2-3/4long mono (C2C) was significantly higher in AS patients than in normal controls. This ratio (CPII/C2C) also correlated with CRP level in AS patients. The CPII/C2C ratio is thought to reflect the balance between collagen synthesis and degradation [36]. Therefore, joint cartilage biomarkers might be another tool for evaluating the AS disease process.
Up to now, investigators have assessed the usefulness of biomarkers for disease activity in AS simply by calculating the correlation between the candidate biomarkers and clinical parameters of disease activity. Actually, just as the correlation coefficient is not a reflection of pathogenesis, the correlation coefficient is not a measurement of the clinical usefulness of candidate biomarkers. Calculations such as the sensitivity and specificity are more important. In addition, to be meaningful in comparing one candidate biomarker with another, P values are needed. As far as we know, our study here is the only one that addresses the question in this way. From the results of ROC curve analysis, MMP-3 was a more useful biomarker compared with ESR and CRP because it was able to provide higher sensitivity and specificity. The AUC values of the ROC curve plots for ESR or CRP are disappointingly only 0.6 or less in both the Taipei and Beijing cohorts. This would suggest that either test provides information only slightly better than chance alone. However, there was some improvement on using MMP-3, with an AUC of 0.74 in the Taipei cohort when the BASDAI cut-off was set at ≥4. Remarkably, the AUC of MMP-3 in the Beijing cohort also reached 0.75 when the BASDAI cut-off was set at ≥5. This was so even when the cohorts were collected by completely different investigators using a completely different translation of the original BASDAI and the ELISA was carried out by completely different laboratory personnel.
In conclusion, serum MMP-3 is a potentially more accurate marker of AS disease activity than ESR and CRP. To validate the usefulness of MMP-3, much larger-scale multicentre studies will be needed. One of the insights that our study provides is that it is not necessary to use values from normal individuals as threshold cut-offs for MMP-3 in AS patients. For analyses of both the Taipei and the Beijing cohorts, we used the cut-off value selected by TG-ROC analysis and the median value as the threshold, respectively. Similar readjustment of threshold values has been made in using high-sensitivity CRP (hs-CRP) to measure the risk of cardiovascular diseases. Large-scale studies show that subjects with CRP levels previously thought to be normal can also be at risk of cardiovascular diseases. This study has not addressed the usefulness of MMP-3 as a biomarker for following AS patients on TNF blockers. Future studies addressing this question may also use the strategy outlined here.
The authors thank Miss Wan-Ting Huang for technical assistance in Taipei and Dr Miansong Zhao for collecting the clinical data from the Beijing cohort.
The authors have declared no conflicts of interest.
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Author notes
1Veterans General Hospital-Taipei and National Yang-Ming Medical University, 2Taipei Medical University-Municipal Wan Fang Hospital, 3National Taipei College of Nursing, Taipei, 4Chung Shan Medical University, Taichung, Taiwan, 5University of California, Los Angeles, CA, USA and 6Chinese PLA General Hospital, Beijing, China.
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