- Email: [email protected]
Association of MMP1, MMP3, MMP9, and MMP12 polymorphisms with risk and clinical course of multiple sclerosis in a Polish population
Journal of Neuroimmunology 214 (2009) 113–117
Contents lists available at ScienceDirect
Journal of Neuroimmunology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j n e u r o i m
Association of MMP1, MMP3, MMP9, and MMP12 polymorphisms with risk and clinical course of multiple sclerosis in a Polish population Dagmara Mirowska-Guzel a,b, Grazyna Gromadzka a,b, Andrzej Czlonkowski b, Anna Czlonkowska a,b,⁎ a b
2nd Department of Neurology, Institute of Psychiatry and Neurology, Sobieskiego 9, 02-957 Warsaw, Poland Department of Clinical and Experimental Pharmacology, Medical University of Warsaw, Krakowskie Przedmiescie 26/28, 00-297 Warsaw, Poland
a r t i c l e
i n f o
Article history: Received 30 December 2008 Received in revised form 16 June 2009 Accepted 17 June 2009 Keywords: Multiple sclerosis MMPs polymorphisms Disease susceptibility PCR
a b s t r a c t Single nucleotide polymorphisms in human MMP genes, including MMP1 (− 1637 1G N 2G), MMP3 (− 1612 5A N 6A), MMP9 (− 1562 C N T), and MMP12 (− 82 A NG), and their impact on multiple sclerosis risk and disease progression in a Polish population were investigated. Increased risk of MS was found among carriers of at least one T allele of MMP9 − 1562 C N T (OR, 1.7; p = 0.0030) and one G allele of MMP12 − 82 A N G (OR, 3.9; p b 0.00001). Additionally, an association between MMP9 genotype and MMP-9 levels in peripheral blood was detected. Our results suggest that MMP9 − 1562 C N T and MMP12 − 82 A NG polymorphisms affect susceptibility to multiple sclerosis. © 2009 Elsevier B.V. All rights reserved.
1. Introduction The pathogenesis and prognosis of multiple sclerosis (MS) are complex and not fully understood. There is some evidence that the disease develops in genetically predisposed individuals, possibly in association with environmental factors (Oksenberg and Barcellos, 2000), and that genetic factors may also determine the clinical course of the disease (Mycko et al., 2004). Currently, there is substantial research interest in single nucleotide polymorphisms (SNP) of many genes potentially involved in MS pathogenesis. Matrix metalloproteinases (MMPs) are proteases that play important roles in remodeling of extracellular matrix (ECM), which comprises about 20% of the central nervous system (CNS; Sobel, 1998). In MS pathogenesis, MMPs have been suggested to promote the influx of inflammatory cells into the brain via disruption of the blood-brain-barrier and to enhance cell migration, leading to myelin degradation, cell death, and axonal loss (reviewed by Milward et al., 2008). MMP-1, MMP-3, MMP-9, and MMP-12 represent different groups of MMPs, namely collagenases, stromielysins, gelatinases, and non-classified MMPs, all of which vary in substrate preference (Ra and Parks, 2007). Until now, only a few articles concerning the involvement of two different MMP9 (Fiotti et al., 2004; Nelissen et al., 2000; Zivkovic et al., 2007; Benešová et al., 2008), MMP2 (Benešová et al., 2008), and MMP3 polymorphisms (Djuric et al., 2008) in MS have been published; however, the data concerning their involvement in MS risk are conflicting. The aim of the
⁎ Corresponding author. Tel.: +48 22 842 76 83; fax: +48 22 842 40 23. E-mail address: [email protected] (A. Czlonkowska). 0165-5728/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jneuroim.2009.06.014
present study was to evaluate polymorphisms in MMP1 (− 1637 1G N 2G), MMP3 (− 1612 5A N 6A), MMP9 (− 1562 C N T), and MMP12 (−82 A NG) and their impact on MS susceptibility and clinical course.
2. Subjects and methods 2.1. Subjects 234 patients (66 men and 168 women) with MS diagnosed according to the McDonald criteria (McDonald et al., 2001; Polman et al., 2005) and 190 unrelated, sex- (76 males and 114 females) and age- (mean age = 40.09 ± 10.19 years) matched healthy controls were qualified to the study. All of the patients and controls were Caucasian, originated from the same middle-eastern region of Poland, and represent a genetically stable and homogenous population; therefore, confounding effects due to migration and race can be excluded. None of the participants were related and no cases of familial MS were included in the study. Disease severity was estimated using the Expanded Disability Status Scale (EDSS; Kurtzke, 1983) and multiple sclerosis severity score (MSSS; Roxburgh et al., 2005). Age of onset and age at diagnosis were included in the analyses. Patient demographics and clinical characteristics are presented in Table 1. Disease course was classified based on clinical data, according to the recommendations of Lublin et al. (1996). A single sample of peripheral blood (PB) was collected into EDTA tubes from all subjects. An additional PB sample was collected from 15 patients to determine MMP-9 concentration. The study protocol was approved by the Local Hospital Ethics Committee.
114
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117
Table 1 Demographic characteristics, clinical data, and MMP1 −1637 1G N 2G, MMP3 −1612 5AN 6A, MMP9 −1562 C N T, MMP12 −82 A N G allele distributions according to clinical course in patients with multiple sclerosis. Parameter
All patients (n = 234)
Sex, female/male % female Age, years (mean ± SD) Age of the first symptoms, years (mean ± SD) Age at MS diagnosis, years (mean ± SD) Disease duration, years (mean ± SD) Median EDSS (min–max) MSSS (mean ± SD) MMP1 1G allele, n (%) MMP3 5A allele, n (%) MMP9 C allele, n (%) MMP12 A allele, n (%)
168/66 72% 37.75 ± 11.05 28.85 ± 9.90
RRMS, n = 192 SPMS, n = 29 PPMS, n = 13 (82%) (13%) (5%) 140/52 73% 35.72 ± 9.92 28.00 ± 9.54
31.72 ± 10.30 31.02 ± 10.19
20/9 69% 46.47 ± 12.22 30.33 ± 9.84
8/5 61% 46.61 ± 10.19 37.54 ± 11.27
32.70 ± 9.21 39.54 ± 11.66
8.91 ± 8.28
7.87 ± 7.18
15.60 ± 11.51
8.69 ± 7.94
3.5 (0.0–9.0) 5.16 ± 2.56 269 (58%) 226 (49%) 362 (77%) 277 (63%)
2.5 (0.0–8.5) 4.73 ± 2.36 216 (56%) 187 (49%) 301 (78%) 235 (61%)
7.0 (3.0–9.0) 7.28 ± 2.67 34 (59%) 28 (48%) 44 (76%) 26 (45%)
4.0 (1.5–7.0) 6.19 ± 2.36 19 (73%) 11 (42%) 17 (65%) 16 (61%)
2.2. MMPs polymorphisms Genomic DNA was isolated using Tri-Reagent (SIGMA, Poland). MMP1 −1637 1GN 2G (rs1799750), MMP3 −1612 5AN 6A (rs3025058), MMP9 −1562 C N T (rs3918244), and MMP12 −82 A NG (rs2276109) genotyping was performed by polymerase chain reaction restriction fragment length polymorphism analysis, as described previously (Dunleavey et al., 2000; Joos et al., 2002; Shan et al., 2006; Zhang et al., 1999; Zhang et al., 2001).
genotypes was lower than expected (3 versus 12, p = 0.02), as was the number of MMP12 − 82 GG homozygotes (8 versus 30, p = 0.0001). As in the cases of MMP9 −1562 C N T and MMP12 −82 A NG, only a few homozygotic carriers of TT and GG genotypes were detected; they were included in the groups of MMP9 CT and MMP12 AG variants, respectively. There were no significant differences in the distributions of MMP polymorphisms between groups of patients with different courses of MS (Table 1). 3.1. Genotypes and susceptibility to MS There were no statistically significant differences in the distributions of the MMP1 − 1637 1G N 2G and MMP3 − 1612 5A N 6A polymorphisms between patients with MS and controls. The frequency of the MMP1 −1637 1G allele was 0.58 in patients with MS and 0.54 in controls (p = 0.13); the frequency of MMP3 − 1612 5A allele was 0.49 in patients with MS and 0.53 in controls (p = 0.28). We found an increased risk of MS associated with the MMP9 − 1562 allele T (p = 0.003; OR, 1.7) and MMP12 − 82 allele G (p b 0.00001; OR, 3.9; Table 2). When combined genotypes including both MMP9 and MMP12 polymorphisms were evaluated, the results were more profound. The combined effects of the −1562 T allele (CT + TT genotype) and − 82 G allele (AG + GG genotype), respectively, significantly increased the risk of MS: 39% MS patients (n = 8; OR, 10.3; p b 0.00001) versus 9.5% controls (n = 18; Table 3). No effect was found for MMP1 − 1637 1G N 2G (2G2G genotype: 14% in patients with MS versus 17.5% in controls, p = 0.32) or MMP3 −1612 5A N 6A (6A6A genotype: 17% in MS patients versus 20% in controls, p = 0.41) with regard to the risk and clinical course of MS. 3.2. Genotype and sex
2.3. MMP-9 levels in peripheral blood The level of MMP-9 in the PB of 15 patients with relapsing– remitting MS in a stable phase of disease (at least 3 months free of relapse or new neurological symptoms), was analyzed using a commercially available enzyme-linked immunosorbent assay (ELISA), according to the manufacturer's instructions (Amersham Pharmacia, Biotrack, USA). 2.4. Statistical analysis Statistical analysis was performed using Statistica PL version 7.1 (StatSoft® Poland, 2006). Genotype and allele frequencies were compared by chi-square test. p ≤ 0.05 was considered statistically significant. Continuous non-dependent data were compared by Mann Whitney Test. The Bonferroni correction for multiple comparisons was used as needed. A multiple logistic regression model expressed as an adjusted odds ratio (OR) and 95% confidence interval (95% CI) was applied to measure the strength of association between genetic polymorphisms and MS. 3. Results Successful genotyping for MMP1 and MMP3 polymorphisms was performed in 230 of 234 samples collected from patients with MS, in 234 samples for MMP9 variants, and in 219 samples for MMP12 polymorphism. In controls, MMP1 and MMP3 polymorphisms were determined in 189 of 190 samples, MMP9 polymorphisms in 190, and MMP12 polymorphisms in 187. In control samples, there was no deviation from Hardy–Weinberg equilibrium for any genotype evaluated. In patients with MS, MMP1 and MMP3 genotype distributions were in accordance with Hardy– Weinberg equilibrium. The number of homozygotic MMP9 − 1562 TT
Genotypes and allele frequencies for −1562 C N T MMP9 and −82 A NG MMP12 variants are shown in Table 4. After Bonferroni correction, no significant differences in allele distributions were found for −1562 C N T MMP9 between female or male patients with MS and healthy volunteers; however, the combination of −1562 MMP9 CT and the TT genotype was significantly more frequent in both female and male patients with MS. Significantly different distributions within alleles and genotypes in both sex groups were found for the −82 A NG MMP12 polymorphism (Table 4). 3.3. Genotypes and clinical parameters Analysis of the effects of different MMP polymorphisms on age of onset, age at disease diagnosis, EDSS or MSSS did not reveal any effect on disease course (data not shown). However, when a group of Table 2 MMP1 −1637 1G N 2G, MMP3 − 1612 5A N 6A, MMP9 − 1562 C N T, and MMP12 − 82 A N G allele and genotype distributions in patients with multiple sclerosis and healthy controls. MS
Controls
MMP9 − 1562 C N T Allele n = 468 T 109 (23%) Genotype n = 234 CT + TT 106 (45%)
n = 380 58 (15%) n = 190 54 (28%)
MMP12 − 82 A NG Allele n = 438 G 161 (37%) Genotype n = 219 GG + AG 153 (70%)
n = 374 49 (13%) n = 187 46 (25%)
⁎ p value counted with chi-square test. ⁎⁎ OR and 95% CI counted with logistic regression.
p value⁎
OR (95%CI)⁎⁎
0.0030
1.7 (1.2–2.4)
0.0004
2.1 (1.4–3.1)
b0.00001
3.9 (2.7–5.5)
b0.00001
7.1 (4.6–11.0)
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117 Table 3 Combined effect of MMP9 − 1562 CT + TT and MMP12 −82 AG + GG variants: comparison of patients with multiple sclerosis and healthy controls.
Genotypes CC and AA CT + TT and AG + GG Other genotypes CC and AG + GG. CT + TT and AA
MS n = 216
Controls n = 190 p value*,b
OR (95% CI)⁎⁎
49 (23%) 85 (39%)
107 (56%) 18 (9.5%)
b0.00001 b0.00001
0.1 (0.1–0.2) 10.3 (5.6–17.0)
82 (38%)
65 (34%)
ns
–
Table 5 Clinical parameters of patients with multiple sclerosis severity score (MSSS) greater than the mean (5.16) according to genotype: MMP9 − 1562 C N T and MMP12 − 82 A NG.
Age, years (mean ± SD) Median EDSS (min–max) Age of onset, years (mean±SD) Age at MS diagnosis, years (mean ± SD) MSSS (mean ± SD)
*p value counted with chi-square test. b p value for significance after Bonferroni correction is 0.017. **OR and 95% CI counted with logistic regression.
patients with MSSS greater than the mean value (MSSS N 5.16) was analyzed, it was found that carriers of MMP9 −1562 CC or MMP12 −82 AA tended to be younger at the time of MS symptom onset as compared to carriers of T allele (CT + TT genotype) or G allele (AG + GG genotype) alleles (Table 5). 3.4. MMP9 −1562 C N T polymorphism and peripheral blood MMP-9 concentration There was a significant difference in the amount of MMP-9 protein in the PB of CC genotype carriers (n = 5; 17.75 ± 8.57 ng/mL) as compared to carriers of at least one T allele (n = 10; 70.88 ± 64.97 ng/ mL; p = 0.027), whereas there were no statistical differences with regard to age of MS onset (27.60 ± 7.86 versus 26.40 ± 7,17 years), median EDSS (3.5 versus 3.0), or MSSS (3.79 ± 2.00 versus 4.19 ± 2.14). 4. Discussion Previous studies evaluating MMPs polymorphisms in MS have focused on polymorphisms in MMP9 (− 1562 C N T and CA microsatellite repeat polymorphisms), MMP2 −1575 G NA and MMP3 −1612 5A N 6A polymorphisms (Fiotti et al., 2004; Nelissen et al., 2000; Zivkovic et al., 2007; Benešová et al., 2008; Djuric et al., 2008); however, these studies did not establish any direct association between any specific genotype and MS susceptibility or clinical course. Fiotti et al. (2004) determined that the presence of more than 22 CA repeats was more common in the MS group than in controls and was correlated with earlier disease onset, whereas Nelissen et al. (2000) found no such association. In turn, Zivkovic et al. (2007)
Table 4 Distribution of MMP9 −1562 C N T and MMP12 − 82 A N G alleles and genotypes in patients with multiple sclerosis and healthy controls according to sex. Women MMP9 MS −1562 C N T n = 168
Men Controls n = 114
pa value
MS n = 66
Controls n = 76
pa value
Allele T
75 (22%) 34 (15%)
0.0300 (nsb) 34 (26%) 24 (16%)
Genotype CT + TT
72 (43%) 32 (28%)
0.0100
34 (52%) 22 (29%) 0.0060
MMP12 − 82 A N G
MS n = 158
pa value
MS n = 61
Allele G
115 (36%) 28 (13%)
b 0.00001
46 (38%) 21 (14%)
b0.00001
Genotype AG + GG
110 (70%) 27 (24%)
b 0.00001
43 (72%) 19 (25%)
b0.00001
a
Controls n = 111
Controls n = 76
0.0400 (nsb)
pa value
p value was counted with chi-square test. b p value after Bonferroni correction not statistically significant in multiply testing for gender sub-groups (p b 0.0125).
115
Age, years (mean ± SD) Median EDSS (min–max) Age of onset, years (mean±SD) Age at MS diagnosis, years (mean ± SD) MSSS (mean ± SD)
MMP9 − 1562 CC (n = 55)
MMP9 −1562 CT+TT (n=44)
p value
37.33 ± 11.06 4.5 (2.0–9.0) 30.05 ± 10.48 31.96 ± 11.30
43.84 ± 9.44 5.25 (2.0–9.0) 35.57 ± 11.00 37.77 ± 10.14
0.0046 ns 0.0121 0.0051
7.67 ± 1.43
7.43 ± 1.47
ns
MMP12 − 82 AA (n = 28)
MMP12 −82 AG+GG (n=66)
p value
33.40 ± 9.47 3.75 (2.0–8.0) 28.57 ± 8.77 30.93 ± 10.61
42.36 ± 10.35 5.0 (2.0–9.0) 34.24 ± 11.63 36.13 ± 11.30
0.0001 0.0129 0.0341 0.0313
7.03 ± 1.44
7.79 ± 1.38
0.0129
identified a trend toward a lower MSSS in MMP9 − 1562T allele carriers, whereas Benešová et al. (2008) noted no association between MMP9 or MMP2 genotypes and EDSS or MSSS. However, it is interesting that both above-mentioned groups (Serbian and Czech) found a significantly less frequent occurrence of the T allele MMP9 −1562 C N T polymorphism in female patients with MS as compared to healthy females, whereas in male patients the difference was not significant. Moreover, Benešová and coworkers described a lower frequency of the MMP9 −1562 T allele in the MS group as a whole than in controls. These results do not correspond with those from our study. In the Polish population, T allele carriership is more frequent in the MS population than in the healthy population (both sexes). Although the frequency of the T allele in controls in Poland is comparable to that observed in Serbia or the Czech Republic (15% versus 17% and 18.2%, respectively), region-specific differences in distribution were observed for MS patients: 23% versus 10% and 11.5%, respectively. The differences in allele frequencies in different European regions could reflect genetic differences within the MS populations or represent the effect of some unknown environmental factors with known geographic differences in distribution. While, such a hypothesis would require both epidemiological and genetic evaluation, it does indicate that such genetic studies need to be performed in different populations. We found no significant association between any of the MMP polymorphisms evaluated and disease progression as measured by MSSS. This result is comparable to that obtained by Benešová et al. (2008) for MMP9 and MMP2 polymorphisms. Herein, we have presented a new data about the contributions of MMP polymorphisms to the risk and clinical course of MS. Carriers of the MMP9 − 1562 T allele or the MMP12 − 82 G allele have a higher MS risk than do non-carriers. Further, when the combined effect of MMP9 and MMP12 variants was taken in account, the MS risk was increased. In contrast, in the group of patients with MSSS greater than the mean, the presence of the MMP9 T allele or the MMP12 G allele had a protective effect with regard to age at disease onset. A similar effect has already described for another autoimmune pathology, Sjögren disease (Hulkkonen et al., 2004). The T allele seemed to protect these patients from Raynaud phenomenon, although no significant difference in MMP9 allele distribution between Sjögren patients and controls was noted. Our results confirmed previously described differences in the level of MMP-9 in the PB of carriers and non-carriers of the MMP9 −1562 T allele. Such an effect is not unexpected because in the MMP-9 gene sequence GCGCAC/TGCC (−1567 to −1559) is a binding site for a transcriptional repressor protein. Interaction between DNA and the repressor protein is impaired by the C N T substitution at −1562,
116
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117
resulting in increased promoter activity in T allele carriers (Zhang et al., 1999). A higher PB MMP-9 level was previously described by Hulkkonen et al. (2004) for MMP9 −1562 TT homozygous patients than for CT or CC polymorphism carriers; however, the difference was not statistically significant. To our knowledge, until now MMP12 −82 A NG variants were not analyzed for either MS risk or disease clinical course. In view of MMP12 function, its polymorphism was expected to be essential in MS pathogenesis. Vos et al. (2003) were one of the first groups to demonstrate the presence of MMP-12 protein in human MS lesions, with special participation in actively demyelinating lesions. Moreover, MMP-12 is known to activate some pro-MMPs, such as MMP-2 and MMP-3, being itself activated by other MMPs. MMP12 − 82 A NG polymorphism may affect MMP12 transcription (Ye, 2000), resulting in interference with the demyelination process. In vitro studies revealed that the −82A to G substitution effects binding affinity of the AP-1 transcription factor and the transcriptional activity of the MMP12 promoter. The more prevalent A allele, with greater affinity for activator protein-1 (AP-1), has higher transcriptional activity in macrophage cell lines (Ye, 2000). As it has been reported that MMP-12 contributes early in myelinogenesis, a lower MMP-12 level due to the more often occurring G allele may play a role in MS susceptibility. Based on the data from studies in MMP9 and MMP12 null mice, it was postulated that both MMPs act through similar mechanisms to regulate myelinogenesis (Larsen et al., 2006), but the results of our present study do not completely support this hypothesis. Our data suggest that high MMP-9 and low MMP-12 levels, as a result of genetic variations, are risk factors for MS. Many recent reports have suggested that MMPs are essential not only for the pathogenesis of CNS pathologies but also for structural and functional recovery (reviewed by Milward et al., 2007). The literature contains many examples of the involvement of MMPs in CNS plasticity, including axon extension by controlling the number of functional axon guidance receptors on the cell surface (Galko and Tessier-Levigne, 2000). It was shown that MMP-9 and MMP-12 are produced by oligodendrocytes in vitro to help regulate their extension (Larsen and Yong, 2004), whereas myelination is delayed in MMP-9 and MMP-12 null mice that exhibit reduced numbers of mature oligodendrocytes, reflecting slower precursor maturation (Larsen et al., 2006). In this aspect, a protective role for the MMP9 − 1562 T allele, which is thought to be responsible for higher concentrations of MMP-9 in the PB of patients with MS, seems reasonable, whereas a protective role for the G allele, which has lower transcriptional activity than the A allele, has not yet been demonstrated in humans. In an experimental autoimmune encephalomyelitis (EAE) model, it was found that MMP-12 null mice achieve a higher peak disease score and maintain it for a longer period of time relative to wild-type mice, and the protective role of MMP-12 was found to be due, at least in part, to a skewed Th1/Th2 ratio (Weaver et al., 2005). DaSilva and Yong (2008) noted that MMP-12 mRNA levels increased before EAE symptoms manifested and that MMP-12 expression peaked during disease progression. They also found MMP-12 expression in areas of demyelination, suggesting a role for MMP-12 in the cleavage of a number of ECM components to permit cell migration. In our MS population, the G allele appeared to be protective only in subjects with the most rapidly progressing disease and only in terms of the age of MS onset. It should be remembered that transcript expression does not necessarily correlate with protein expression (Anthony et al., 1998; DaSilva and Yong, 2008). Thus, our results concerning the association between the −82 G NA MMP12 polymorphism and MS susceptibility and age of disease onset needs further evaluation. It needs to be verified whether there is a significant difference in MMP12 in the PB of different genotype carriers and whether this difference is reflected in CNS infiltration by MMP-12 positive cells. The observed lack of effect of MMP3 −1612 5A N 6A polymorphisms is in line with the results previously published by Djuric et al.
(2008). As well, the frequencies of MMP3 −1612 5A N 6A alleles and genotypes found in the present study are comparable to those reported by Djuric and coworkers. Although our study is the first to show an association between polymorphisms in both MMP9 and MMP12 and MS in a Polish population that is relatively homogenous and stable, the sample size is an important limitation of the study. The small number of patients and controls limits statistical significance of determination an exact genetic effect. However, this report is the first to evaluate multiple MMP polymorphisms in MS. Additional studies are needed to validate our results, with special attention given to the association between genotype and clinical disease course. Acknowledgments We thank Ms. Marzena Zdan for excellent technical support. This study was supported by a grant from Warsaw Medical University, 1M9/W2/07-09. References Anthony, D.C., Miller, K.M., Fearn, S., Townsend, M.J., Opdenakker, G., Wells, G.M., Clements, J.M., Chandler, S., Gearing, A.J., Perry, V.H., 1998. Matrix metalloproteinase expression in an experimentally-induced DTH model of multiple sclerosis in the rat CNS. J. Neuroimmunol. 87, 62–72. Benešová, Y., Vašku, A., Štourač, P., Hladíková, M., Beránek, M., Kadaňka, Z., Novotná, H., Bednařík, J., 2008. Matrix metalloproteinase-9 and matrix metalloproteinase-2 gene polymorphisms in multiple sclerosis. J. Neuroimmunol. 205, 105–108. DaSilva, A.G., Yong, V.W., 2008. Expression and regulation of matrix metalloproteinase12 in experimental autoimmune encephalomyelitis and by bone marrow derived macrophages in vitro. J. Neuroimmunol. 199, 24–34. Djuric, T., Zivkovic, M., Stankovic, A., Dincic, E., Raicevic, R., Alavantic, D., 2008. Association of the MMP-3 5A/6A gene polymorphism with multiple sclerosis in patients from Serbia. J. Neurol. Sci. 267, 62–65. Dunleavey, L., Beyzzade, S., Ye, S., 2000. Rapid genotype analysis of stromyelisin gene 5A/6A polymorphism. Atherosclerosis 151, 587–589. Fiotti, N., Zivadinov, R., Altamura, N., Nasuelli, D., Bratina, A., Tommasi, M.A., Bosco, A., Locatelli, L., Grop, A., Cazzato, G., Guarnieri, G., Giansante, C., Zorzon, M., 2004. MMP-9 microsatellite polymorphism and multiple sclerosis. J. Neuroimmunol. 152, 147–151. Galko, M.J., Tessier-Levigne, M., 2000. Function of an axonal chemoattractant modulated by metalloproteinase activity. Science 289, 1365–1367. Hulkkonen, J., Pertovaara, M., Antonen, J., Pasternack, A., Hurme, M., Pollanen, P., Lehtimaki, T., 2004. Matrix-metalloproteinase-9 (MMP-9) gene polymorphism and MMP-9 plasma levels in primary Sjögren syndrome. Rheumatology 43, 1476–1479. Joos, L., He, J.Q., Shepherdson, M.B., Connett, J.E., Anthonisen, N.R., Paré, P.D., Sandford, A.J., 2002. The role of matrix metalloproteinase polymorphisms in the rate of decline in lung function. Hum. Mol. Genet. 11, 569–576. Kurtzke, J.F., 1983. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33, 1444–1452. Larsen, P.H., Yong, V.W., 2004. The expression of matrix metalloproteinase-12 by oligodendrocytes regulates their maturation and morphological differentiation. J. Neurosci. 24, 7597–7603. Larsen, P.H., DaSilva, A.G., Contant, K., Yong, V.W., 2006. Myelin formation during development of the CNS is delayed in matrix metalloproteinase-9 and -12 null mice. J. Neurosci. 26, 2207–2214. Lublin, F.D., Reingold, S.C., for the National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis, 1996. Defining the clinical course of multiple sclerosis: results of an international survey. National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis. Neurology 46, 907–911. McDonald, W.I., Compston, A., Edan, G., Goodkin, D., Hartung, H.P., Lublin, F.D., McFarland, H.F., Paty, D.W., Polman, C.H., Reingold, S.C., Sandberg-Wollheim, M., Sibley, W., Thompson, A., van den Noort, S., Weinshenker, B.Y., Wolinsky, J.S., 2001. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann. Neurol. 50, 121–127. Milward, E.A., Fitzsimmons, C., Szklarczyk, A., Conant, K., 2007. The matrix metalloproteinases in CNS plasticity; an overview. J. Neuroimmunol. 187, 9–19. Milward, E.A., Kim, K.J., Szklarczyk, A., Nguyen, T., Melli, G., Nayak, M., Deshpande, D., Fitzsimmons, C., Hoke, A., Kerr, D., Griffin, J.W., Calabresi, P.A., Conant, K., 2008. Cleavage of myelin associated glycoprotein by matrix metalloproteinases. J. Neuroimmunol. 193, 140–148. Mycko, M., Papoian, R., Boschert, U., Raine, C.S., Selmaj, K.W., 2004. Microarray gene expression profiling of chronic active and inactive lesions in multiple sclerosis. Clin. Neurol. Neurosurg. 106, 223–229. Nelissen, I., Vandenbroeck, K., Fiten, P., Hillert, J., Olsson, T., Marrosu, M.G., Opdenakker, G., 2000. Polymorphism analysis suggests that the gelatinase B gene is not a susceptibility factor for multiple sclerosis. J. Neuroimmunol. 105, 58–63. Oksenberg, J.R., Barcellos, L.F., 2000. The complex genetic aetiology for multiple sclerosis. J. NeuroVirol. 6, 10–14.
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117 Polman, Ch.H., Reingold, S.C., Edan, G., Filippi, M., Hartung, H.-P., Kappos, L., Lublin, F.D., Metz, L.M., McFarland, H.F., O'Connor, P.W., Sandberg-Wollheim, M., Thompson, A.J., Weinshenker, B.G., Wolinsky, J.S., 2005. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann. Neurol. 58, 840–846. Ra, H.-J., Parks, W.C., 2007. Control of matrix metalloproteinase catalytic activity. Matrix Biol. 26, 587–596. Roxburgh, R.H.S.R, Seaman, S.R., Masterman, T., Hensiek, A.E., Sawcer, S.J., Vukusic, S., Achiti, I., Confavreux, C., Coustans, M., le Page, E., Eden, G., McDonnell, G.V., Hawkins, S., Trojano, M., Liguori, M., Cocco, E., Marrosu, M.G., Tesser, F., Leone, M.A., Weber, A., Zipp, F., Miterski, B., Epplen, J.T., Oturai, A., Soelberg Sorensen, P., Celius, E.G., Téllez Lara, N., Montalban, X., Villoslada, P., Silva, A.M., Marta, M., Leite, I., Dubois, B., Rubio, J., Butzkueven, H., Kilpatrick, T., Mycko, M.P., Selmaj, K.W., Rio, M.E., Sá, M., Salemi, G., Savettieri, G., Hillert, J., Compston, D.A.S., 2005. Multiple sclerosis severity score. Using disability and disease duration to rate disease severity. Neurology 64, 1144–1151. Shan, K., Lian-Fu, Z., Hui, D., Wei, G., Na, W., Xia, J., Yan, L., 2006. Polymorphisms in the promoter regions of the matrix metalloproteinases-7, -9 and the risk of endometriosis and adenomyosis in China. Mol. Hum. Reprod. 12, 35–39. Sobel, R.A., 1998. The extracellular matrix in multiple sclerosis lesions. J. Neuropathol. Exp. Neurol. 57 (3), 205–217.Polman, Ch.H., Reingold, S.C., Edan, G., Filippi, M., Hartung, H.-P., Kappos, L., Lublin, F.D., Metz, L.M., McFarland, H.F., O'Connor, P.W., Sandberg-Wollheim, M., Thompson, A.J., Weinshenker, B.G., Wolinsky, J.S., 2005.
117
Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann. Neurol. 58, 840–846. Vos, C.M.P., van Haastert, E.S., de Groot, C.J.A., van der Valk, P., de Vries, H.E., 2003. Matrix metalloproteinase-12 is expressed in phagocytic macrophages in active multiple sclerosis lesion. J. Neuroimmunol. 138, 106–114. Weaver, A., DaSilva, A.G., Nuttall, R.K., Edwards, D.R., Shapiro, S.D., Rivest, S., Yong, V.W., 2005. An elevated matrix metalloproteinase (MMP) in an animal model of multiple sclerosis is protective by affecting Th1/Th2 polarization. FASEB J. 19, 1668–1670. Ye, S., 2000. Polymorphism in matrix metalloproteinase gene promoters: implication in regulation of gene expression and susceptibility of various diseases. Matrix Biol. 19, 623–629. Zhang, B., Ye, S., Herrmann, S.M., Eriksson, P., de Maat, M., Evans, A., Arveiler, D., Luc, G., Cambien, F., Hamsten, A., Watkins, H., Henney, A.M., 1999. Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis. Circulation 99, 1788–1794. Zhang, B., Dhillon, S., Geary, I., Howell, W.M., Iannotti, F., Day, I.N., Ye, S., 2001. Polymorphisms in matrix metalloproteinase-1, -3, -9, and -12 genes in relation to subarachnoid hemorrhage. Stroke 32, 2198–2202. Zivkovic, M., Djuric, T., Dincic, E., Raicevic, R., Alavantic, D., Stankovic, A., 2007. Matrix metalloproteinase-9-1562 C/T gene polymorphisms In Serbian patients with multiple sclerosis. J. Neuroimmunol. 189, 147–150.
Contents lists available at ScienceDirect
Journal of Neuroimmunology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j n e u r o i m
Association of MMP1, MMP3, MMP9, and MMP12 polymorphisms with risk and clinical course of multiple sclerosis in a Polish population Dagmara Mirowska-Guzel a,b, Grazyna Gromadzka a,b, Andrzej Czlonkowski b, Anna Czlonkowska a,b,⁎ a b
2nd Department of Neurology, Institute of Psychiatry and Neurology, Sobieskiego 9, 02-957 Warsaw, Poland Department of Clinical and Experimental Pharmacology, Medical University of Warsaw, Krakowskie Przedmiescie 26/28, 00-297 Warsaw, Poland
a r t i c l e
i n f o
Article history: Received 30 December 2008 Received in revised form 16 June 2009 Accepted 17 June 2009 Keywords: Multiple sclerosis MMPs polymorphisms Disease susceptibility PCR
a b s t r a c t Single nucleotide polymorphisms in human MMP genes, including MMP1 (− 1637 1G N 2G), MMP3 (− 1612 5A N 6A), MMP9 (− 1562 C N T), and MMP12 (− 82 A NG), and their impact on multiple sclerosis risk and disease progression in a Polish population were investigated. Increased risk of MS was found among carriers of at least one T allele of MMP9 − 1562 C N T (OR, 1.7; p = 0.0030) and one G allele of MMP12 − 82 A N G (OR, 3.9; p b 0.00001). Additionally, an association between MMP9 genotype and MMP-9 levels in peripheral blood was detected. Our results suggest that MMP9 − 1562 C N T and MMP12 − 82 A NG polymorphisms affect susceptibility to multiple sclerosis. © 2009 Elsevier B.V. All rights reserved.
1. Introduction The pathogenesis and prognosis of multiple sclerosis (MS) are complex and not fully understood. There is some evidence that the disease develops in genetically predisposed individuals, possibly in association with environmental factors (Oksenberg and Barcellos, 2000), and that genetic factors may also determine the clinical course of the disease (Mycko et al., 2004). Currently, there is substantial research interest in single nucleotide polymorphisms (SNP) of many genes potentially involved in MS pathogenesis. Matrix metalloproteinases (MMPs) are proteases that play important roles in remodeling of extracellular matrix (ECM), which comprises about 20% of the central nervous system (CNS; Sobel, 1998). In MS pathogenesis, MMPs have been suggested to promote the influx of inflammatory cells into the brain via disruption of the blood-brain-barrier and to enhance cell migration, leading to myelin degradation, cell death, and axonal loss (reviewed by Milward et al., 2008). MMP-1, MMP-3, MMP-9, and MMP-12 represent different groups of MMPs, namely collagenases, stromielysins, gelatinases, and non-classified MMPs, all of which vary in substrate preference (Ra and Parks, 2007). Until now, only a few articles concerning the involvement of two different MMP9 (Fiotti et al., 2004; Nelissen et al., 2000; Zivkovic et al., 2007; Benešová et al., 2008), MMP2 (Benešová et al., 2008), and MMP3 polymorphisms (Djuric et al., 2008) in MS have been published; however, the data concerning their involvement in MS risk are conflicting. The aim of the
⁎ Corresponding author. Tel.: +48 22 842 76 83; fax: +48 22 842 40 23. E-mail address: [email protected] (A. Czlonkowska). 0165-5728/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.jneuroim.2009.06.014
present study was to evaluate polymorphisms in MMP1 (− 1637 1G N 2G), MMP3 (− 1612 5A N 6A), MMP9 (− 1562 C N T), and MMP12 (−82 A NG) and their impact on MS susceptibility and clinical course.
2. Subjects and methods 2.1. Subjects 234 patients (66 men and 168 women) with MS diagnosed according to the McDonald criteria (McDonald et al., 2001; Polman et al., 2005) and 190 unrelated, sex- (76 males and 114 females) and age- (mean age = 40.09 ± 10.19 years) matched healthy controls were qualified to the study. All of the patients and controls were Caucasian, originated from the same middle-eastern region of Poland, and represent a genetically stable and homogenous population; therefore, confounding effects due to migration and race can be excluded. None of the participants were related and no cases of familial MS were included in the study. Disease severity was estimated using the Expanded Disability Status Scale (EDSS; Kurtzke, 1983) and multiple sclerosis severity score (MSSS; Roxburgh et al., 2005). Age of onset and age at diagnosis were included in the analyses. Patient demographics and clinical characteristics are presented in Table 1. Disease course was classified based on clinical data, according to the recommendations of Lublin et al. (1996). A single sample of peripheral blood (PB) was collected into EDTA tubes from all subjects. An additional PB sample was collected from 15 patients to determine MMP-9 concentration. The study protocol was approved by the Local Hospital Ethics Committee.
114
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117
Table 1 Demographic characteristics, clinical data, and MMP1 −1637 1G N 2G, MMP3 −1612 5AN 6A, MMP9 −1562 C N T, MMP12 −82 A N G allele distributions according to clinical course in patients with multiple sclerosis. Parameter
All patients (n = 234)
Sex, female/male % female Age, years (mean ± SD) Age of the first symptoms, years (mean ± SD) Age at MS diagnosis, years (mean ± SD) Disease duration, years (mean ± SD) Median EDSS (min–max) MSSS (mean ± SD) MMP1 1G allele, n (%) MMP3 5A allele, n (%) MMP9 C allele, n (%) MMP12 A allele, n (%)
168/66 72% 37.75 ± 11.05 28.85 ± 9.90
RRMS, n = 192 SPMS, n = 29 PPMS, n = 13 (82%) (13%) (5%) 140/52 73% 35.72 ± 9.92 28.00 ± 9.54
31.72 ± 10.30 31.02 ± 10.19
20/9 69% 46.47 ± 12.22 30.33 ± 9.84
8/5 61% 46.61 ± 10.19 37.54 ± 11.27
32.70 ± 9.21 39.54 ± 11.66
8.91 ± 8.28
7.87 ± 7.18
15.60 ± 11.51
8.69 ± 7.94
3.5 (0.0–9.0) 5.16 ± 2.56 269 (58%) 226 (49%) 362 (77%) 277 (63%)
2.5 (0.0–8.5) 4.73 ± 2.36 216 (56%) 187 (49%) 301 (78%) 235 (61%)
7.0 (3.0–9.0) 7.28 ± 2.67 34 (59%) 28 (48%) 44 (76%) 26 (45%)
4.0 (1.5–7.0) 6.19 ± 2.36 19 (73%) 11 (42%) 17 (65%) 16 (61%)
2.2. MMPs polymorphisms Genomic DNA was isolated using Tri-Reagent (SIGMA, Poland). MMP1 −1637 1GN 2G (rs1799750), MMP3 −1612 5AN 6A (rs3025058), MMP9 −1562 C N T (rs3918244), and MMP12 −82 A NG (rs2276109) genotyping was performed by polymerase chain reaction restriction fragment length polymorphism analysis, as described previously (Dunleavey et al., 2000; Joos et al., 2002; Shan et al., 2006; Zhang et al., 1999; Zhang et al., 2001).
genotypes was lower than expected (3 versus 12, p = 0.02), as was the number of MMP12 − 82 GG homozygotes (8 versus 30, p = 0.0001). As in the cases of MMP9 −1562 C N T and MMP12 −82 A NG, only a few homozygotic carriers of TT and GG genotypes were detected; they were included in the groups of MMP9 CT and MMP12 AG variants, respectively. There were no significant differences in the distributions of MMP polymorphisms between groups of patients with different courses of MS (Table 1). 3.1. Genotypes and susceptibility to MS There were no statistically significant differences in the distributions of the MMP1 − 1637 1G N 2G and MMP3 − 1612 5A N 6A polymorphisms between patients with MS and controls. The frequency of the MMP1 −1637 1G allele was 0.58 in patients with MS and 0.54 in controls (p = 0.13); the frequency of MMP3 − 1612 5A allele was 0.49 in patients with MS and 0.53 in controls (p = 0.28). We found an increased risk of MS associated with the MMP9 − 1562 allele T (p = 0.003; OR, 1.7) and MMP12 − 82 allele G (p b 0.00001; OR, 3.9; Table 2). When combined genotypes including both MMP9 and MMP12 polymorphisms were evaluated, the results were more profound. The combined effects of the −1562 T allele (CT + TT genotype) and − 82 G allele (AG + GG genotype), respectively, significantly increased the risk of MS: 39% MS patients (n = 8; OR, 10.3; p b 0.00001) versus 9.5% controls (n = 18; Table 3). No effect was found for MMP1 − 1637 1G N 2G (2G2G genotype: 14% in patients with MS versus 17.5% in controls, p = 0.32) or MMP3 −1612 5A N 6A (6A6A genotype: 17% in MS patients versus 20% in controls, p = 0.41) with regard to the risk and clinical course of MS. 3.2. Genotype and sex
2.3. MMP-9 levels in peripheral blood The level of MMP-9 in the PB of 15 patients with relapsing– remitting MS in a stable phase of disease (at least 3 months free of relapse or new neurological symptoms), was analyzed using a commercially available enzyme-linked immunosorbent assay (ELISA), according to the manufacturer's instructions (Amersham Pharmacia, Biotrack, USA). 2.4. Statistical analysis Statistical analysis was performed using Statistica PL version 7.1 (StatSoft® Poland, 2006). Genotype and allele frequencies were compared by chi-square test. p ≤ 0.05 was considered statistically significant. Continuous non-dependent data were compared by Mann Whitney Test. The Bonferroni correction for multiple comparisons was used as needed. A multiple logistic regression model expressed as an adjusted odds ratio (OR) and 95% confidence interval (95% CI) was applied to measure the strength of association between genetic polymorphisms and MS. 3. Results Successful genotyping for MMP1 and MMP3 polymorphisms was performed in 230 of 234 samples collected from patients with MS, in 234 samples for MMP9 variants, and in 219 samples for MMP12 polymorphism. In controls, MMP1 and MMP3 polymorphisms were determined in 189 of 190 samples, MMP9 polymorphisms in 190, and MMP12 polymorphisms in 187. In control samples, there was no deviation from Hardy–Weinberg equilibrium for any genotype evaluated. In patients with MS, MMP1 and MMP3 genotype distributions were in accordance with Hardy– Weinberg equilibrium. The number of homozygotic MMP9 − 1562 TT
Genotypes and allele frequencies for −1562 C N T MMP9 and −82 A NG MMP12 variants are shown in Table 4. After Bonferroni correction, no significant differences in allele distributions were found for −1562 C N T MMP9 between female or male patients with MS and healthy volunteers; however, the combination of −1562 MMP9 CT and the TT genotype was significantly more frequent in both female and male patients with MS. Significantly different distributions within alleles and genotypes in both sex groups were found for the −82 A NG MMP12 polymorphism (Table 4). 3.3. Genotypes and clinical parameters Analysis of the effects of different MMP polymorphisms on age of onset, age at disease diagnosis, EDSS or MSSS did not reveal any effect on disease course (data not shown). However, when a group of Table 2 MMP1 −1637 1G N 2G, MMP3 − 1612 5A N 6A, MMP9 − 1562 C N T, and MMP12 − 82 A N G allele and genotype distributions in patients with multiple sclerosis and healthy controls. MS
Controls
MMP9 − 1562 C N T Allele n = 468 T 109 (23%) Genotype n = 234 CT + TT 106 (45%)
n = 380 58 (15%) n = 190 54 (28%)
MMP12 − 82 A NG Allele n = 438 G 161 (37%) Genotype n = 219 GG + AG 153 (70%)
n = 374 49 (13%) n = 187 46 (25%)
⁎ p value counted with chi-square test. ⁎⁎ OR and 95% CI counted with logistic regression.
p value⁎
OR (95%CI)⁎⁎
0.0030
1.7 (1.2–2.4)
0.0004
2.1 (1.4–3.1)
b0.00001
3.9 (2.7–5.5)
b0.00001
7.1 (4.6–11.0)
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117 Table 3 Combined effect of MMP9 − 1562 CT + TT and MMP12 −82 AG + GG variants: comparison of patients with multiple sclerosis and healthy controls.
Genotypes CC and AA CT + TT and AG + GG Other genotypes CC and AG + GG. CT + TT and AA
MS n = 216
Controls n = 190 p value*,b
OR (95% CI)⁎⁎
49 (23%) 85 (39%)
107 (56%) 18 (9.5%)
b0.00001 b0.00001
0.1 (0.1–0.2) 10.3 (5.6–17.0)
82 (38%)
65 (34%)
ns
–
Table 5 Clinical parameters of patients with multiple sclerosis severity score (MSSS) greater than the mean (5.16) according to genotype: MMP9 − 1562 C N T and MMP12 − 82 A NG.
Age, years (mean ± SD) Median EDSS (min–max) Age of onset, years (mean±SD) Age at MS diagnosis, years (mean ± SD) MSSS (mean ± SD)
*p value counted with chi-square test. b p value for significance after Bonferroni correction is 0.017. **OR and 95% CI counted with logistic regression.
patients with MSSS greater than the mean value (MSSS N 5.16) was analyzed, it was found that carriers of MMP9 −1562 CC or MMP12 −82 AA tended to be younger at the time of MS symptom onset as compared to carriers of T allele (CT + TT genotype) or G allele (AG + GG genotype) alleles (Table 5). 3.4. MMP9 −1562 C N T polymorphism and peripheral blood MMP-9 concentration There was a significant difference in the amount of MMP-9 protein in the PB of CC genotype carriers (n = 5; 17.75 ± 8.57 ng/mL) as compared to carriers of at least one T allele (n = 10; 70.88 ± 64.97 ng/ mL; p = 0.027), whereas there were no statistical differences with regard to age of MS onset (27.60 ± 7.86 versus 26.40 ± 7,17 years), median EDSS (3.5 versus 3.0), or MSSS (3.79 ± 2.00 versus 4.19 ± 2.14). 4. Discussion Previous studies evaluating MMPs polymorphisms in MS have focused on polymorphisms in MMP9 (− 1562 C N T and CA microsatellite repeat polymorphisms), MMP2 −1575 G NA and MMP3 −1612 5A N 6A polymorphisms (Fiotti et al., 2004; Nelissen et al., 2000; Zivkovic et al., 2007; Benešová et al., 2008; Djuric et al., 2008); however, these studies did not establish any direct association between any specific genotype and MS susceptibility or clinical course. Fiotti et al. (2004) determined that the presence of more than 22 CA repeats was more common in the MS group than in controls and was correlated with earlier disease onset, whereas Nelissen et al. (2000) found no such association. In turn, Zivkovic et al. (2007)
Table 4 Distribution of MMP9 −1562 C N T and MMP12 − 82 A N G alleles and genotypes in patients with multiple sclerosis and healthy controls according to sex. Women MMP9 MS −1562 C N T n = 168
Men Controls n = 114
pa value
MS n = 66
Controls n = 76
pa value
Allele T
75 (22%) 34 (15%)
0.0300 (nsb) 34 (26%) 24 (16%)
Genotype CT + TT
72 (43%) 32 (28%)
0.0100
34 (52%) 22 (29%) 0.0060
MMP12 − 82 A N G
MS n = 158
pa value
MS n = 61
Allele G
115 (36%) 28 (13%)
b 0.00001
46 (38%) 21 (14%)
b0.00001
Genotype AG + GG
110 (70%) 27 (24%)
b 0.00001
43 (72%) 19 (25%)
b0.00001
a
Controls n = 111
Controls n = 76
0.0400 (nsb)
pa value
p value was counted with chi-square test. b p value after Bonferroni correction not statistically significant in multiply testing for gender sub-groups (p b 0.0125).
115
Age, years (mean ± SD) Median EDSS (min–max) Age of onset, years (mean±SD) Age at MS diagnosis, years (mean ± SD) MSSS (mean ± SD)
MMP9 − 1562 CC (n = 55)
MMP9 −1562 CT+TT (n=44)
p value
37.33 ± 11.06 4.5 (2.0–9.0) 30.05 ± 10.48 31.96 ± 11.30
43.84 ± 9.44 5.25 (2.0–9.0) 35.57 ± 11.00 37.77 ± 10.14
0.0046 ns 0.0121 0.0051
7.67 ± 1.43
7.43 ± 1.47
ns
MMP12 − 82 AA (n = 28)
MMP12 −82 AG+GG (n=66)
p value
33.40 ± 9.47 3.75 (2.0–8.0) 28.57 ± 8.77 30.93 ± 10.61
42.36 ± 10.35 5.0 (2.0–9.0) 34.24 ± 11.63 36.13 ± 11.30
0.0001 0.0129 0.0341 0.0313
7.03 ± 1.44
7.79 ± 1.38
0.0129
identified a trend toward a lower MSSS in MMP9 − 1562T allele carriers, whereas Benešová et al. (2008) noted no association between MMP9 or MMP2 genotypes and EDSS or MSSS. However, it is interesting that both above-mentioned groups (Serbian and Czech) found a significantly less frequent occurrence of the T allele MMP9 −1562 C N T polymorphism in female patients with MS as compared to healthy females, whereas in male patients the difference was not significant. Moreover, Benešová and coworkers described a lower frequency of the MMP9 −1562 T allele in the MS group as a whole than in controls. These results do not correspond with those from our study. In the Polish population, T allele carriership is more frequent in the MS population than in the healthy population (both sexes). Although the frequency of the T allele in controls in Poland is comparable to that observed in Serbia or the Czech Republic (15% versus 17% and 18.2%, respectively), region-specific differences in distribution were observed for MS patients: 23% versus 10% and 11.5%, respectively. The differences in allele frequencies in different European regions could reflect genetic differences within the MS populations or represent the effect of some unknown environmental factors with known geographic differences in distribution. While, such a hypothesis would require both epidemiological and genetic evaluation, it does indicate that such genetic studies need to be performed in different populations. We found no significant association between any of the MMP polymorphisms evaluated and disease progression as measured by MSSS. This result is comparable to that obtained by Benešová et al. (2008) for MMP9 and MMP2 polymorphisms. Herein, we have presented a new data about the contributions of MMP polymorphisms to the risk and clinical course of MS. Carriers of the MMP9 − 1562 T allele or the MMP12 − 82 G allele have a higher MS risk than do non-carriers. Further, when the combined effect of MMP9 and MMP12 variants was taken in account, the MS risk was increased. In contrast, in the group of patients with MSSS greater than the mean, the presence of the MMP9 T allele or the MMP12 G allele had a protective effect with regard to age at disease onset. A similar effect has already described for another autoimmune pathology, Sjögren disease (Hulkkonen et al., 2004). The T allele seemed to protect these patients from Raynaud phenomenon, although no significant difference in MMP9 allele distribution between Sjögren patients and controls was noted. Our results confirmed previously described differences in the level of MMP-9 in the PB of carriers and non-carriers of the MMP9 −1562 T allele. Such an effect is not unexpected because in the MMP-9 gene sequence GCGCAC/TGCC (−1567 to −1559) is a binding site for a transcriptional repressor protein. Interaction between DNA and the repressor protein is impaired by the C N T substitution at −1562,
116
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117
resulting in increased promoter activity in T allele carriers (Zhang et al., 1999). A higher PB MMP-9 level was previously described by Hulkkonen et al. (2004) for MMP9 −1562 TT homozygous patients than for CT or CC polymorphism carriers; however, the difference was not statistically significant. To our knowledge, until now MMP12 −82 A NG variants were not analyzed for either MS risk or disease clinical course. In view of MMP12 function, its polymorphism was expected to be essential in MS pathogenesis. Vos et al. (2003) were one of the first groups to demonstrate the presence of MMP-12 protein in human MS lesions, with special participation in actively demyelinating lesions. Moreover, MMP-12 is known to activate some pro-MMPs, such as MMP-2 and MMP-3, being itself activated by other MMPs. MMP12 − 82 A NG polymorphism may affect MMP12 transcription (Ye, 2000), resulting in interference with the demyelination process. In vitro studies revealed that the −82A to G substitution effects binding affinity of the AP-1 transcription factor and the transcriptional activity of the MMP12 promoter. The more prevalent A allele, with greater affinity for activator protein-1 (AP-1), has higher transcriptional activity in macrophage cell lines (Ye, 2000). As it has been reported that MMP-12 contributes early in myelinogenesis, a lower MMP-12 level due to the more often occurring G allele may play a role in MS susceptibility. Based on the data from studies in MMP9 and MMP12 null mice, it was postulated that both MMPs act through similar mechanisms to regulate myelinogenesis (Larsen et al., 2006), but the results of our present study do not completely support this hypothesis. Our data suggest that high MMP-9 and low MMP-12 levels, as a result of genetic variations, are risk factors for MS. Many recent reports have suggested that MMPs are essential not only for the pathogenesis of CNS pathologies but also for structural and functional recovery (reviewed by Milward et al., 2007). The literature contains many examples of the involvement of MMPs in CNS plasticity, including axon extension by controlling the number of functional axon guidance receptors on the cell surface (Galko and Tessier-Levigne, 2000). It was shown that MMP-9 and MMP-12 are produced by oligodendrocytes in vitro to help regulate their extension (Larsen and Yong, 2004), whereas myelination is delayed in MMP-9 and MMP-12 null mice that exhibit reduced numbers of mature oligodendrocytes, reflecting slower precursor maturation (Larsen et al., 2006). In this aspect, a protective role for the MMP9 − 1562 T allele, which is thought to be responsible for higher concentrations of MMP-9 in the PB of patients with MS, seems reasonable, whereas a protective role for the G allele, which has lower transcriptional activity than the A allele, has not yet been demonstrated in humans. In an experimental autoimmune encephalomyelitis (EAE) model, it was found that MMP-12 null mice achieve a higher peak disease score and maintain it for a longer period of time relative to wild-type mice, and the protective role of MMP-12 was found to be due, at least in part, to a skewed Th1/Th2 ratio (Weaver et al., 2005). DaSilva and Yong (2008) noted that MMP-12 mRNA levels increased before EAE symptoms manifested and that MMP-12 expression peaked during disease progression. They also found MMP-12 expression in areas of demyelination, suggesting a role for MMP-12 in the cleavage of a number of ECM components to permit cell migration. In our MS population, the G allele appeared to be protective only in subjects with the most rapidly progressing disease and only in terms of the age of MS onset. It should be remembered that transcript expression does not necessarily correlate with protein expression (Anthony et al., 1998; DaSilva and Yong, 2008). Thus, our results concerning the association between the −82 G NA MMP12 polymorphism and MS susceptibility and age of disease onset needs further evaluation. It needs to be verified whether there is a significant difference in MMP12 in the PB of different genotype carriers and whether this difference is reflected in CNS infiltration by MMP-12 positive cells. The observed lack of effect of MMP3 −1612 5A N 6A polymorphisms is in line with the results previously published by Djuric et al.
(2008). As well, the frequencies of MMP3 −1612 5A N 6A alleles and genotypes found in the present study are comparable to those reported by Djuric and coworkers. Although our study is the first to show an association between polymorphisms in both MMP9 and MMP12 and MS in a Polish population that is relatively homogenous and stable, the sample size is an important limitation of the study. The small number of patients and controls limits statistical significance of determination an exact genetic effect. However, this report is the first to evaluate multiple MMP polymorphisms in MS. Additional studies are needed to validate our results, with special attention given to the association between genotype and clinical disease course. Acknowledgments We thank Ms. Marzena Zdan for excellent technical support. This study was supported by a grant from Warsaw Medical University, 1M9/W2/07-09. References Anthony, D.C., Miller, K.M., Fearn, S., Townsend, M.J., Opdenakker, G., Wells, G.M., Clements, J.M., Chandler, S., Gearing, A.J., Perry, V.H., 1998. Matrix metalloproteinase expression in an experimentally-induced DTH model of multiple sclerosis in the rat CNS. J. Neuroimmunol. 87, 62–72. Benešová, Y., Vašku, A., Štourač, P., Hladíková, M., Beránek, M., Kadaňka, Z., Novotná, H., Bednařík, J., 2008. Matrix metalloproteinase-9 and matrix metalloproteinase-2 gene polymorphisms in multiple sclerosis. J. Neuroimmunol. 205, 105–108. DaSilva, A.G., Yong, V.W., 2008. Expression and regulation of matrix metalloproteinase12 in experimental autoimmune encephalomyelitis and by bone marrow derived macrophages in vitro. J. Neuroimmunol. 199, 24–34. Djuric, T., Zivkovic, M., Stankovic, A., Dincic, E., Raicevic, R., Alavantic, D., 2008. Association of the MMP-3 5A/6A gene polymorphism with multiple sclerosis in patients from Serbia. J. Neurol. Sci. 267, 62–65. Dunleavey, L., Beyzzade, S., Ye, S., 2000. Rapid genotype analysis of stromyelisin gene 5A/6A polymorphism. Atherosclerosis 151, 587–589. Fiotti, N., Zivadinov, R., Altamura, N., Nasuelli, D., Bratina, A., Tommasi, M.A., Bosco, A., Locatelli, L., Grop, A., Cazzato, G., Guarnieri, G., Giansante, C., Zorzon, M., 2004. MMP-9 microsatellite polymorphism and multiple sclerosis. J. Neuroimmunol. 152, 147–151. Galko, M.J., Tessier-Levigne, M., 2000. Function of an axonal chemoattractant modulated by metalloproteinase activity. Science 289, 1365–1367. Hulkkonen, J., Pertovaara, M., Antonen, J., Pasternack, A., Hurme, M., Pollanen, P., Lehtimaki, T., 2004. Matrix-metalloproteinase-9 (MMP-9) gene polymorphism and MMP-9 plasma levels in primary Sjögren syndrome. Rheumatology 43, 1476–1479. Joos, L., He, J.Q., Shepherdson, M.B., Connett, J.E., Anthonisen, N.R., Paré, P.D., Sandford, A.J., 2002. The role of matrix metalloproteinase polymorphisms in the rate of decline in lung function. Hum. Mol. Genet. 11, 569–576. Kurtzke, J.F., 1983. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33, 1444–1452. Larsen, P.H., Yong, V.W., 2004. The expression of matrix metalloproteinase-12 by oligodendrocytes regulates their maturation and morphological differentiation. J. Neurosci. 24, 7597–7603. Larsen, P.H., DaSilva, A.G., Contant, K., Yong, V.W., 2006. Myelin formation during development of the CNS is delayed in matrix metalloproteinase-9 and -12 null mice. J. Neurosci. 26, 2207–2214. Lublin, F.D., Reingold, S.C., for the National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis, 1996. Defining the clinical course of multiple sclerosis: results of an international survey. National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis. Neurology 46, 907–911. McDonald, W.I., Compston, A., Edan, G., Goodkin, D., Hartung, H.P., Lublin, F.D., McFarland, H.F., Paty, D.W., Polman, C.H., Reingold, S.C., Sandberg-Wollheim, M., Sibley, W., Thompson, A., van den Noort, S., Weinshenker, B.Y., Wolinsky, J.S., 2001. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann. Neurol. 50, 121–127. Milward, E.A., Fitzsimmons, C., Szklarczyk, A., Conant, K., 2007. The matrix metalloproteinases in CNS plasticity; an overview. J. Neuroimmunol. 187, 9–19. Milward, E.A., Kim, K.J., Szklarczyk, A., Nguyen, T., Melli, G., Nayak, M., Deshpande, D., Fitzsimmons, C., Hoke, A., Kerr, D., Griffin, J.W., Calabresi, P.A., Conant, K., 2008. Cleavage of myelin associated glycoprotein by matrix metalloproteinases. J. Neuroimmunol. 193, 140–148. Mycko, M., Papoian, R., Boschert, U., Raine, C.S., Selmaj, K.W., 2004. Microarray gene expression profiling of chronic active and inactive lesions in multiple sclerosis. Clin. Neurol. Neurosurg. 106, 223–229. Nelissen, I., Vandenbroeck, K., Fiten, P., Hillert, J., Olsson, T., Marrosu, M.G., Opdenakker, G., 2000. Polymorphism analysis suggests that the gelatinase B gene is not a susceptibility factor for multiple sclerosis. J. Neuroimmunol. 105, 58–63. Oksenberg, J.R., Barcellos, L.F., 2000. The complex genetic aetiology for multiple sclerosis. J. NeuroVirol. 6, 10–14.
D. Mirowska-Guzel et al. / Journal of Neuroimmunology 214 (2009) 113–117 Polman, Ch.H., Reingold, S.C., Edan, G., Filippi, M., Hartung, H.-P., Kappos, L., Lublin, F.D., Metz, L.M., McFarland, H.F., O'Connor, P.W., Sandberg-Wollheim, M., Thompson, A.J., Weinshenker, B.G., Wolinsky, J.S., 2005. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann. Neurol. 58, 840–846. Ra, H.-J., Parks, W.C., 2007. Control of matrix metalloproteinase catalytic activity. Matrix Biol. 26, 587–596. Roxburgh, R.H.S.R, Seaman, S.R., Masterman, T., Hensiek, A.E., Sawcer, S.J., Vukusic, S., Achiti, I., Confavreux, C., Coustans, M., le Page, E., Eden, G., McDonnell, G.V., Hawkins, S., Trojano, M., Liguori, M., Cocco, E., Marrosu, M.G., Tesser, F., Leone, M.A., Weber, A., Zipp, F., Miterski, B., Epplen, J.T., Oturai, A., Soelberg Sorensen, P., Celius, E.G., Téllez Lara, N., Montalban, X., Villoslada, P., Silva, A.M., Marta, M., Leite, I., Dubois, B., Rubio, J., Butzkueven, H., Kilpatrick, T., Mycko, M.P., Selmaj, K.W., Rio, M.E., Sá, M., Salemi, G., Savettieri, G., Hillert, J., Compston, D.A.S., 2005. Multiple sclerosis severity score. Using disability and disease duration to rate disease severity. Neurology 64, 1144–1151. Shan, K., Lian-Fu, Z., Hui, D., Wei, G., Na, W., Xia, J., Yan, L., 2006. Polymorphisms in the promoter regions of the matrix metalloproteinases-7, -9 and the risk of endometriosis and adenomyosis in China. Mol. Hum. Reprod. 12, 35–39. Sobel, R.A., 1998. The extracellular matrix in multiple sclerosis lesions. J. Neuropathol. Exp. Neurol. 57 (3), 205–217.Polman, Ch.H., Reingold, S.C., Edan, G., Filippi, M., Hartung, H.-P., Kappos, L., Lublin, F.D., Metz, L.M., McFarland, H.F., O'Connor, P.W., Sandberg-Wollheim, M., Thompson, A.J., Weinshenker, B.G., Wolinsky, J.S., 2005.
117
Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann. Neurol. 58, 840–846. Vos, C.M.P., van Haastert, E.S., de Groot, C.J.A., van der Valk, P., de Vries, H.E., 2003. Matrix metalloproteinase-12 is expressed in phagocytic macrophages in active multiple sclerosis lesion. J. Neuroimmunol. 138, 106–114. Weaver, A., DaSilva, A.G., Nuttall, R.K., Edwards, D.R., Shapiro, S.D., Rivest, S., Yong, V.W., 2005. An elevated matrix metalloproteinase (MMP) in an animal model of multiple sclerosis is protective by affecting Th1/Th2 polarization. FASEB J. 19, 1668–1670. Ye, S., 2000. Polymorphism in matrix metalloproteinase gene promoters: implication in regulation of gene expression and susceptibility of various diseases. Matrix Biol. 19, 623–629. Zhang, B., Ye, S., Herrmann, S.M., Eriksson, P., de Maat, M., Evans, A., Arveiler, D., Luc, G., Cambien, F., Hamsten, A., Watkins, H., Henney, A.M., 1999. Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis. Circulation 99, 1788–1794. Zhang, B., Dhillon, S., Geary, I., Howell, W.M., Iannotti, F., Day, I.N., Ye, S., 2001. Polymorphisms in matrix metalloproteinase-1, -3, -9, and -12 genes in relation to subarachnoid hemorrhage. Stroke 32, 2198–2202. Zivkovic, M., Djuric, T., Dincic, E., Raicevic, R., Alavantic, D., Stankovic, A., 2007. Matrix metalloproteinase-9-1562 C/T gene polymorphisms In Serbian patients with multiple sclerosis. J. Neuroimmunol. 189, 147–150.