Hum. Reprod. Advance Access published online on February 28, 2008
Human Reproduction, doi:10.1093/humrep/den007
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Genetic polymorphisms of matrix metalloproteinase 12 and 13 genes are implicated in endometriosis progression
1 Université Paris Descartes, Assistance Publique-Hôpitaux de Paris, Service de Gynécologie–Obstétrique II, CHU Cochin-Saint Vincent de Paul, Paris, France 2 Equipe 21, Institut Cochin, Faculté de Médecine Paris 5, Université Paris Descartes, CNRS (UMR 8104), 24 rue du Faubourg Saint-Jacques, 75014 Paris, France 3 Inserm, U567, Paris, France 4 Inserm, U535, Villejuif, France 5 Université Paris Sud, IFR 69, UMR-S535, Villejuif, France
6 Correspondence address. E-mail: borghese{at}cochin.inserm.fr
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Abstract |
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BACKGROUND: Matrix metalloproteinases (MMPs) may contribute to endometriosis. We tested whether eight functional polymorphisms of these genes could modify the risk of endometriosis.
METHODS: In this case–control study, 227 endometriosis and 241 controls were genotyped for MMP1 –1607 1G/2G, MMP2 –1575 G/A (MMP2.1), –1306 C/T (MMP2.2), MMP3 –1612 5A/6A, MMP7 –153 C/T (MMP7.1), –181 A/G (MMP7.2), MMP12 –82 A/G and MMP13–77 A/G. Association between MMP genotypes and superficial (SUP), deep infiltrating (DIE) and endometriomas (OMA) was tested for each polymorphism separately, using unconditional logistic regression and then for combined genotypes, using the combination test.
RESULTS: When considering all cases, MMP2 polymorphisms were found to be significant, mainly due to DIE (P = 0.023). A small difference between SUP and controls was found for MMP7.2 (P = 0.032) and MMP12 (P = 0.035), in the absence of correction for multiple testing. Using the combination test, the best association when comparing SUP with controls was obtained for MMP12–MMP13 (P = 0.004) for the combined genotype A/G–A/A (odds ratio = 27.60, 95% confidence interval: 2.80–272.40).
CONCLUSIONS: These data show a potential role for MMP12 –82 A/G and MMP13 –77 A/G combined polymorphisms in superficial endometriosis. As no association was found with deep infiltrating endometriosis, this combination of polymorphisms might protect from a more in-depth penetration of tissues.
Key words: endometriosis/matrix metalloproteinase/polymorphism/combination test/genetics
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Introduction |
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Endometriosis is a common gynecological disease that affects up to 10% of women in their reproductive years. It is defined as the presence of endometrial tissue (i.e. glandular and stromal cells) outside the uterine cavity. Main symptoms are pelvic pain and infertility, two conditions that greatly deteriorate quality of life (Giudice and Kao, 2004
). Few things are known concerning the physiopathology of the disease. The most widely accepted theory for the development of endometriosis is the implantation theory of Sampson (1927), who proposed that endometrial tissue is retrogradely shed through the Fallopian tubes into the peritoneal cavity during menstruation, where it attaches and proliferates at ectopic sites. This theory explains the anatomical distribution of the lesions (Chapron et al., 2006). But it fails to give an acceptable answer to the puzzling fact that almost 90% of women have a menstrual reflux (Halme et al., 1984), whereas only 10% have endometriosis. Although most women may have some retrograde menstrual flow, typically their immune system is able to clear the debris and prevent implantation and growth of cells from this occurrence. However, in some patients, endometrial tissue transplanted by retrograde menstruation is able to implant and establish itself as endometriosis (Sampson, 1927).
One explanation could come from genetic facts and hereditary factors. It is well recognized that daughters or sisters of patients with endometriosis are at higher risk of developing endometriosis themselves (Bischoff and Simpson, 2004). Familial studies in the early 1970s clearly demonstrated a familial aggregation, with an estimated recurrence risk between 5% and 8% for all first-degree relatives (Ranney, 1971; Simpson et al., 1980). More recently, an Australian study investigated heritability of endometriosis by assessing concordance between monozygotic and dizygotic twins and suggested that 51% of the variance of the latent liability to endometriosis might be attributable to additive genetic influences (Treloar et al., 1999). Although no segregation study was carried out, endometriosis is thus regarded as a multifactorial and polygenetic disorder that is thought to result from an interaction between a person's genetic makeup and various environmental triggers, like many common diseases such as diabetes mellitus or essential hypertension (Bischoff and Simpson, 2004).
One approach to better understand the mechanisms of endometriosis is to identify disease-susceptibility genes. A genetic-linkage study has recently implicated a locus on chromosome 10q26 in the predisposition to endometriosis, focusing on the genes located in this region, like PTEN and EMX2 (Treloar et al., 2005). Genetic association studies have revealed that several genetic variants, including those of progesterone and estrogen receptors and detoxification genes, could increase the risk of endometriosis (Georgiou et al., 1999; Wieser et al., 2002). However, the results of these studies remain controversial (Guo, 2005). No consensus on their implications can be worked out, mainly because of the limited size of the study populations, the ethnic diversity of polymorphisms and complicating environmental factors.
Mammalian matrix metalloproteinases (MMPs) belong to a large group of 23 proteases, which share a conserved domain structure. MMPs have been found up-regulated in cancer and high levels of MMPs often correlated with poor prognosis (Egeblad and Werb, 2002). However, the relationship between MMPs and cancer is not so simple, e.g. increased MMP activity can enhance tumor progression or can inhibit it (Coussens et al., 2002). It has thus focused attention on MMPs and pathology, and relatively less on the normal physiological roles of these enzymes. MMPs typically regulate tissue remodeling, by degrading structural components of the extracellular matrix (ECM). But, MMPs can also affect basic cellular functions (proliferation, differentiation, motility, apoptosis, etc.) by regulating the ECM proteins with which the cells interact (Page-McCaw et al., 2007).
Endometriosis shares some characteristics with cancer, such as clonality, ability to invade surrounding tissues and maybe capacity to metastasize (Somigliana et al., 2006; Noel et al., 2007). High levels of MMPs, including MMP1, MMP2 and MMP3, were found in ectopic endometrium, when compared with eutopic endometrium (Osteen et al., 2003). There is also persistent expression of MMP7 and MMP12 in the eutopic endometrium during the secretory phase, whereas normally they are suppressed by progesterone (Osteen et al., 1999). Moreover, suppression of metalloproteinase activity inhibits the formation of ectopic lesions in nude mice (Bruner et al., 1997). This led to the conclusion that misexpression of matrix-degrading enzymes might enable retrograde endometrial tissue to invade the peritoneal surface.
Genetic polymorphisms located in the promoter region of the MMP genes could lead to increased gene expression and could be associated with predisposition to various diseases (Ye, 2006). In this case–control study, we examined the possible association between eight MMP polymorphisms and the risk of endometriosis. Moreover, we further investigated their role in endometriosis penetration depth, by comparing each type of endometriosis (superficial, deep infiltrating and ovarian) separately.
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Materials and Methods |
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Study population and ethics
This case–control study was conducted between March 2004 and June 2006. The data were obtained from 468 unrelated women of reproductive age operated in the gynecological surgery unit of Cochin University Hospital (Paris, France).
The 227 patients with endometriosis all underwent laparoscopy or laparotomy and had histologically confirmed diagnosis. These patients were divided into three categories considering the most severe lesion (Somigliana et al., 2007): ovarian endometriosis or endometriomas (OMA) (n = 64), superficial endometriosis (SUP) (n = 24) and deep infiltrating endometriosis (DIE) (n = 139), defined as endometriosis infiltrating deeper than 5 mm under the peritoneal surface (Koninckx et al., 1991).
The 241 control subjects without endometriosis were also recruited in the same surgery unit. They consisted of women without any lesion suggesting endometriosis during comprehensive surgical exploration, including a thorough observation of reproductive organs, appendix, small and large bowel, peritoneum and diaphragm. These patients were mainly operated for infertility work-up, symptomatic uterine fibroids and benign ovarian cysts, other than endometriomas.
Ethnicity was based on self-report and categorized as Caucasian (n = 351), African (n = 95), Asian (n = 19) and unknown (n = 3). Thus, further statistical analysis was adjusted on population group, and if not possible (for combination test), limited to the Caucasian population.
All patients and controls gave their written informed consent and the study protocol was approved by the local ethical committee (CCPPRB of Paris-Cochin).
Selection of polymorphisms
With the use of public databases, including National Center for Biotechnology Information, and previously published studies (Ye, 2006), we selected eight single nucleotide polymorphisms (SNPs) of the MMP genes: MMP1 –1607 1G/2G, MMP2 –1575 G/A (MMP2.1), MMP2 –1306 C/T (MMP2.2), MMP3 –1612 5A/6A, MMP7 –153 C/T (MMP7.1), MMP7 –181 A/G (MMP7.2), MMP12, –82 A/G and MMP13 –77 A/G—all of them in the promoter regions—that cause changes in the level of transcription and/or expression of the encoded protein, as described in Table I. The minus signs before the numbered nucleotide in some polymorphisms, such as –1607 1G/2G in Table I, refer to the 5' upstream region relative to the transcription-initiation site of a gene.
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Genotyping of polymorphisms
Five milliliters of whole venous blood was collected from each subject into tubes containing EDTA. Immediately after collection, samples were stored at +4°C until use. Genomic DNA was isolated from whole blood using MagNa Pure Compact Nucleic Acid Isolation Kit (Roche Applied Science) and DNA quantification was performed with Quant-It DNA Assay Kit (Molecular Probes).
The eight MMP polymorphisms were studied by real-time PCR allelic discrimination assay on ABI 7900 HT Sequence Detection System (Applied Biosystem). A mix containing specific primers and probes for each allele (respectively labeled with fluorescent reporter dyes VIC and FAM), designed by Applied Biosystem (Taqman SNP Genotyping Assay), was used. Briefly, reactions were performed in 5 µl comprising 10 ng of DNA, 20x Mix of specific primers and probes and 2x TaqMan Universal PCR Master Mix (Applied Biosystem). Primer sequences were indicated in Table I.
For a negative control, samples containing distilled water instead of DNA were systematically included in each MMP genotyping plate.
Statistical analysis
Homogeneity of allele frequencies among population groups was tested using a 
2 statistic or Fisher's exact test. Hardy–Weinberg proportions were tested for each polymorphism. Linkage disequilibrium (LD) between closely linked pairwise loci was estimated using the measure r2 (Hill and Robertson, 1968; Ohta and Kimura, 1969), i.e. MMP1, MMP3, MMP7.1, MMP7.2, MMP12 and MMP13 on chromosome 11 on the one hand and MMP2.1 and MMP2.2 on chromosome 16 on the other hand.
Association was first tested for each polymorphism separately. For each polymorphism, genotype-specific odds ratio (OR) and 95% confidence intervals (CI) were computed using unconditional logistic regression adjusted on matching factors and Wald test was used to assess the global effect of this SNP. The homozygous genotype for the allele resulting in the highest level of expression of the encoded protein was set as the reference class, except for MMP7.1 and MMP7.2 for which the most frequent allele was taken as the reference one, as the identification of the most functional allele was not possible. Tests of homogeneity and unconditional logistic regression were done using SAS v9.1.
The association was further examined using the method developed by Jannot et al. (2003) that allows for the analysis of all possible combinations of 1 to n tightly linked SNPs in order to test their association with the disease. For each SNP combination, the method computes a statistic test contrasting the genotypic distribution between cases and controls. With six studied SNPs on the MMP cluster on chromosome 11, six tests are performed for single SNP, 15 tests for combinations of two SNPs, 20 for combinations of three SNPs and so on, giving a total of 63 performed tests for all possible combinations of SNPs. Because all these tests are correlated (many of them are nested in each others, and the SNPs are likely to be in LD), a permutation procedure is implemented which displays a significance level adequately adjusted for multiple testing (Becker and Knapp, 2004). In a second step, among the significantly associated combinations, the most parsimonious one can be identified by comparing nested combinations using 2 tests.
As the combination test does not yet allow an estimation of OR, when association was significant, the risks associated with the different combinations of genotypes were estimated using unconditional logistic regression.
A value of P < 0.05 was considered significant.
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Results |
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The characteristics of the study population are presented in Table II. The allele frequencies for each marker among controls of each population group are listed in Table III. Comparisons were performed only between the Caucasian and African groups as Asian controls were too few to allow a statistical comparison. For several polymorphisms, allele frequencies were found to be significantly different according to ethnic origin (MMP2.1, MMP2.2, MMP3 and MMP12). Therefore, tests of Hardy–Weinberg proportions were performed separately for the African and Caucasian groups and were not performed for the Asian population. The distribution of genotypes for the eight polymorphisms was in agreement with Hardy–Weinberg proportions in both populations. Various degrees of LD was found between polymorphisms within the chromosome 11 cluster in the African and the Caucasian populations, as presented in Table IV. This LD was found to be very strong between polymorphisms of the MMP2 gene both in the African (r2 = 0.79) and in the Caucasian populations (r2 = 0.98).
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Results of analyses for single polymorphisms are shown in Table V. All ORs were adjusted on ethnic origin. When considering all cases of endometriosis, only MMP2.1 and MMP2.2 were found to be significant at the 5% level but the degree of significance was not very high. As these polymorphisms are strongly correlated, only one of them (MMP2.1) was taken into account. The difference between patients and controls appeared to be mainly due to the DIE patients (P = 0.023). On the other hand, a small difference between patients with SUP and controls was found for MMP7.2 and MMP12.
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As the combination test does not allow an adjustment on confounders, it was performed for the six polymorphisms on chromosome 11 only for Caucasians who are the most important group. When considering all patients with endometriosis compared with controls, no combination appeared significant. The same results were obtained for the OMA and DIE patients. A clearly significant result was obtained for the comparison of the SUP patients to the controls. Seven combinations appeared significant and the global significance of the test was 0.002 (Table VI). Tests of nested combinations showed that all the significant ones could be due to the MMP12–MMP13 combination.
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The association between combined MMP12–MMP13 genotypes and SUP endometriosis was confirmed by logistic regression (Table VII). The AA–AG and AA–GG genotypes had to be pooled because the latter was absent in patients. The combination comprising the GG genotype of MMP12 was not considered because it was almost absent in patients as well in controls. We found an opposite effect of the AA–(AG or GG) genotypes (OR = 0.1, 95% CI 0.0–0.9) and AG–AA genotype (OR = 27.6, 95% CI 2.8–272.4).
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Discussion |
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We investigated the role of MMP1, MMP2, MMP3, MMP7, MMP12 and MMP13 polymorphisms as endometriosis risk factors in a case–control study of cases with SUP (n = 24), DIE (n = 139) and OMA (n = 64). These polymorphisms are known to modulate transcriptional activity.
When considering single SNP polymorphisms, only MMP2.1 was associated with an increased risk of all types of endometriosis, more specifically of DIE (P = 0.023). This association did not hold when multiple testing was accounted for. Hence, one could only suspect a tendency to a possible association between MMP2 polymorphisms and endometriosis, which is consistent with a growing body of evidence that gave a pivotal role for MMP2 in endometriosis, especially in DIE (Uzan et al., 2004; Kim et al., 2007).
When considering each type of endometriosis separately, only MMP7 –181 A/G and MMP12 –82 A/G polymorphisms were found to be slightly associated with superficial endometriosis (P = 0.032 and 0.035, respectively). However, conclusions must be considered with caution. Once again, the degree of significance was not very high, but the decreased risk associated with the MMP7 G allele was consistent with previous findings. Indeed, as MMP7 gene was found induced in ectopic endometrium (Bruner-Tran et al., 2002), we expected that the –181G allele, leading to an increased protein expression (Jormsjo et al., 2001), could be a susceptibility factor for endometriosis, as recently described by Shan et al. (2006) in a population of 219 patients and 160 controls from North China. These authors had previously established that MMP1 –1607 1G/2G and MMP1–MMP3 2G/6A haplotype might modify susceptibility to the disease in the same population (Shan et al., 2005). In the present study, mainly based on a Caucasian population, our results did not confirm these findings, but are consistent with another association study which did not find any relation between MMP1 and MMP3 polymorphisms and genetic predisposition to endometriosis in an Italian population (Ferrari et al., 2006).
The most interesting results were provided by the combination test. This test has been shown to be particularly powerful to detect the effect of polymorphisms when several polymorphisms interact with low marginal effect of each SNP and when one of the SNPs masks the expression of the other ones (Jannot et al., 2003). Indeed, the combination test revealed a strong effect of the MMP12–MMP13 A/G–A/A combined genotype. These results suggest that MMP13 polymorphism, which was not found to influence endometriosis risk when taken alone, may have a role by interacting with the effect of MMP12. This finding underlines the importance of using the combination test for demonstrating combined effects of polymorphisms with little or no individual effect.
The MMP12 polymorphism, and especially the MMP12–MMP13 A/G–A/A combined genotype, might thus play a role at the earliest step of endometriosis by promoting the development of peritoneal implants. However, the following steps of endometriosis development, in particular DIE or OMA, should require the contribution of other factors. These factors could mask the effect of MMP12–MMP13 combined genotype and explain the absence of association when DIE patients and OMA patients are compared with controls. A similar mechanism was hypothesized by Lievre et al. (2006), who found an association of MMP1–MMP3 with small adenomas of the colon, compared with polyp-free controls, but not for large adenomas. Another possible mechanism could be that MMP12 gene, in association with MMP13 gene, would act as a modifying gene for an unknown factor, genetic or environmental, and would only influence the type of endometriosis, which would explain why the association was not found for the other types of endometriosis. This combination of polymorphisms seems to block the disease at the superficial stage and not to allow a more in-depth penetration. However, these preliminary results must be taken with caution and have to be confirmed.
To our knowledge, this is the first study on the relationship between the MMP12 and the MMP13 polymorphisms and the susceptibility to endometriosis. The role of MMP13 is not well documented, except its involvement in bone development and repair (Yamagiwa et al., 1999; Inada et al., 2004). Results from in vitro transfection experiments with MMP13 –77 A/G polymorphism showed that the constructs with A had twice as much transcriptional activity as the constructs with G at the same position (Yoon et al., 2002). In addition, this polymorphism was associated with susceptibility to atherosclerosis (Yoon et al., 2002). On the other hand, MMP12 may inhibit angiogenesis through cleavage of plasminogen and collagen 13, resulting in the generation of angiostatin and endostatin, which have an angiostatic effect (Dong et al., 1997; Cornelius et al., 1998; Egeblad and Werb, 2002). Selected MMP12-null mouse mutant phenotypes revealed increased angiogenesis due to decreased angiostatin (Houghton et al., 2006). MMP12 is also involved in the cleavage of domain D1 of urokinase-type plasminogen activator cellular receptor, which is responsible for cell migration during tumor invasion and angiogenesis (Koolwijk et al., 2001). The –82 A/G polymorphism is located in the activator protein-1 (AP-1) transcription factor binding site. A lower binding affinity of AP-1 to the G allele was associated with lower MMP-12 promoter activity in vitro in transient transfection studies (Jormsjo et al., 2000). Our data suggest that lower expressing GG genotype was associated with SUP, an effect that was heightened when combined with MMP13 A/A genotype. A potential explanation is that loss of angiostatic effects of MMP12 preferentially promotes the development of endometriosis, in which the implication of angiogenesis was recognized a long time ago (Oosterlynck et al., 1993; McLaren et al., 1996). These speculations should be taken with caution and the mechanisms underlying the potential involvement of MMP12 polymorphism in endometriosis remain to be clearly determined. In the future, it would be particularly interesting to assess the MMP12 and MMP13 expression levels in superficial endometriotic implants and to test if selective modulation of these two proteases could promote establishment of peritoneal ectopic lesions in existing experimental models of endometriosis (Grummer, 2006).
In summary, genetic variations in the MMP family, especially a combination of MMP12 and MMP13 polymorphisms, may contribute to the development of endometriosis in a Caucasian population. Further studies of the biological ramifications of these polymorphisms may add to our understanding of the biology of the disease and provide potential foci for targeted therapies.
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Funding |
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Funds for the study reported here were provided by the Institut National de la Santé et de la Recherche Médicale (INSERM) and the Assistance Publique - Hôpitaux de Paris (AP-HP).
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Submitted on October 2, 2007; resubmitted on November 14, 2007; accepted on November 28, 2007.
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