Skip to main content
Journal of Assisted Reproduction and Genetics logoLink to Journal of Assisted Reproduction and Genetics
. 2016 Dec 17;34(3):365–371. doi: 10.1007/s10815-016-0848-4

Functional single nucleotide polymorphisms of matrix metalloproteinase 7 and 12 genes in idiopathic recurrent spontaneous abortion

Anita Barišić 1, Nina Pereza 1, Alenka Hodžić 2, Miljenko Kapović 1, Borut Peterlin 2, Saša Ostojić 1,
PMCID: PMC5360680  PMID: 27987113

Abstract

Purpose

The aim of this study was to investigate the potential association of matrix metalloproteinase 7 (MMP7) -181 A/G and MMP12 -82 A/G functional single nucleotide polymorphisms (SNP) with idiopathic recurrent spontaneous abortion (IRSA) in Slovenian reproductive couples.

Methods

A case–control study was conducted on 149 couples with 3 or more consecutive idiopathic spontaneous pregnancy loses and 149 women and men with at least 2 live births and no history of pregnancy complications. Genotyping of MMP7 -181 A/G and MMP12 -82 A/G SNPs was performed using polymerase chain reaction and restriction fragment length polymorphism methods.

Results

There were no statistically significant differences in the distribution of MMP7 -181 A/G and MMP12 -82 A/G genotype, allele, or haplotype frequencies between IRSA patients and controls, as well as patients’ primary and secondary IRSA. We also found no association of MMP7 -181 A/G and MMP12 -82 A/G genotypes, alleles, and haplotypes with IRSA.

Conclusions

We found no evidence to support the association between IRSA and MMP7 -181 A/G and MMP12 -82 A/G SNPs in Slovenian reproductive couples.

Keywords: Single nucleotide polymorphisms, Pregnancy, Recurrent spontaneous abortion, Matrix metalloproteinases

Introduction

Idiopathic recurrent spontaneous abortion (IRSA) is defined as the spontaneous loss of three or more consecutive pregnancies [1]. This pregnancy complication, which occurs mostly during early gestation, is an intriguing phenomenon for clinicians and scientists due to the fact that the cause cannot be determined in 50–60% of couples [13].

Successful embryo implantation depends on a receptive endometrium and functional blastocyst, as well as a coordinated dialogue between them [4]. During the secretory phase, including the implantation window and decidual transformation, the expression profiles of endometrial genes are changed considerably compared to proliferative phase [58]. It has been suggested that abnormalities in gene expression during the secretory phase may lead to inappropriate endometrial development and, consequently, various reproductive disorders, including recurrent spontaneous abortion [912].

A key event in endometrial decidualization, trophoblast implantation, and placentation is the degradation and remodeling of the extracellular matrix (ECM), which is determined by a careful balance between matrix synthesis, modification, and degradation [13]. Matrix-degrading enzymes include a large family of matrix metalloproteinases (MMPs), which comprises 23 endopeptidases in humans [14].

During pregnancy, MMPs are secreted by both endometrial and trophoblast cells [15, 16]. Earlier studies have reported alterations in the expression of several MMP genes in women with IRSA and their spontaneously aborted conceptuses compared to women with normal pregnancies, which can lead to an altered ECM turnover [10, 12, 1724]. In addition, we previously evaluated the potential association of MMP1, 2, 3, and 9 functional single nucleotide polymorphisms (SNP) with IRSA and found a statistically significant increased frequency of the MMP2 -735 CT and MMP9 -1562 CC genotypes in IRSA women compared to controls, suggesting that these might be risk genotypes for IRSA [25]. In the present study, we extended this analysis to MMP7 and 12 genes, both of which exert important functions in pregnancy, including implantation and remodeling of spiral arteries. Additionally, polymorphisms in these genes have been investigated in different disorders, including gynecological [2628] and non-gynecological cancers [2931], as well as reproductive disorders [32, 33] and various systemic disorders [3436]. Our aim was to evaluate the potential association between IRSA in Slovenian reproductive couples and MMP7 -181 A/G and MMP12 -82 A/G functional SNPs, which are located in gene promoter regions.

Materials and methods

Subjects

A case–control study was performed to examine the potential association of MMP7 -181 A/G and MMP12 -82 A/G SNPs with IRSA in Slovenian reproductive couples.

The study was approved by the Slovenian and Croatian National Ethics’ Committees, and each participant provided written informed consent prior to entering the study. All participants were recruited through the Institute of Medical Genetics, Department of Obstetrics and Gynecology, University Medical Center, Ljubljana, Slovenia.

The IRSA group included 149 women and their 149 partners with a history of 3 or more consecutive miscarriages before the 22nd week of gestation, the etiology of which could not be explained by conventional criteria for RSA evaluation [1]. Exclusion criteria for RSA couples were chromosome aberrations in either partner, and, additionally in women, endocrine or metabolic disorders, autoimmune diseases or other systemic disorders, antiphospholipid syndrome, previous venous or arterial thrombosis, and uterine anatomic abnormalities. A total of 98 (65.8%) of couples had no live births (primary IRSA), whereas 51 (34.2%) had at least one live-born child (secondary IRSA). One hundred thirty-eight couples (92.6%) had at least 3 SAs, and 11 had 4 or more SAs (7.4%). In addition, 92% of couples had the SAs in the first trimester and 8% in the second trimester. Median age of IRSA women and men was 33 (range 23–46) and 34 (range 23–54), respectively.

The control group consisted of 149 unrelated healthy men and 149 unrelated healthy women with at least 2 normal term deliveries and no previous history of SA or any other reproductive disorder.

Molecular genetic methods

Genomic DNA of IRSA couples and control subjects was extracted from peripheral blood leukocytes by standard procedures using a commercially available kit (QIAGEN FlexiGene DNA kit, QIAGEN, Hilden, Germany). Extracted DNA was stored at −20 °C.

Genotyping of MMP7 -181 A/G and MMP12 -82 A/G SNPs was performed using the combination of polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) methods. Conditions were taken from previous studies and were slightly modified [26, 29] (Table 1). Polymerase chain reaction was carried in thermal cyclers (Mastercycle Personal, Eppendorf, Hamburg, Germany and 2720 Thermal Cycler, Applied Biosystems, Carlsbad, CA, USA). The PCR products and restriction fragments were visualized under ultraviolet light after electrophoresis on 1 and 3% agarose gels stained with GelRed (Olerup SSP, Saltsjobaden, Sweden), respectively. The presence of specific genotypes was determined by the band of expected size.

Table 1.

Conditions for genotyping of MMP7 -181 A/G and MMP12 -82 A/G SNPs

Gene (chromosome locus) SNP Primers PCR reaction conditions PCR product Restriction enzyme Restriction products
MMP7 (11q22.2) -181 A/G
(rs11568818)
5′-TGGTACCATAATGTCCTGAATG-3′ 94 °C (5 min) 150 bp EcoRia
5′-TCGTTATTGGCAGGAAGCACACAATGAATT-3′ 35×: 94 °C (30 s) / 47 °C (30 s) / 72 °C (30 s) AA: 150 bp
72 °C (5 min) AG: 150 + 120 + 30 bp
GG: 120 + 30 bp
MMP12 (11q22.2) -82 A/G
(rs2276109)
5′-CTTCTAAACGGATCAATTCAG-3′ 95 °C (5 min) 137 bp PVulla AA: 137 bp
5′-GTCAAGGGATGATATCAGCT-3′ 35×: 94 °C (30 s) / 45 °C (30 s) / 72 °C (30 s) AG: 137 + 119 + 18 bp
72 °C (10 min) GG: 119 + 18 bp

aNew England BioLabs, MA, USA

Statistical analysis

Statistical power was calculated using DSS Researcher’s Toolkit (www.dssresearch.com/toolkit/spcalc/power_p2.asp). Hardy–Weinberg equilibrium was calculated using Simple Hardy–Weinberg Calculator—Court Lab (Washington State University College of Veterinary Medicine, Pullman, WA, USA). Haplotype frequencies were calculated using SNP analyzer Pro™ (version 1.8.581.342-2009-06-18, Istech Corp., CEO, Korea). Differences in genotype, allele, and haplotype frequencies between patients and controls were determined using chi-square test (Statistica for Windows, version 12, Statsoft, Inc., Tulsa, OK, USA). Associations of individual and combined MMP7 -181 A/G and MMP12 -82 A/G genotypes, alleles, and haplotypes with IRSA were estimated by calculating odds ratios (ORs) and their 95% confidence intervals (CIs) (Medcalc for Windows, version 14.12.0, Medcalc Software, Mariakerke, Belgium). P values ≤0.05 were considered statistically significant.

Results

The power of the present study was 98% to detect a 1.5-fold increase in the frequency of the MMP7 -181G allele and 90% to detect a 2.0-fold increase in the frequency of the MMP12 -82G alleles, respectively. Genotyping was unsuccessful in two men with IRSA, who were excluded from further analysis. The frequencies of MMP7 -181 A/G and MMP12 -82 A/G genotypes and alleles in IRSA and control groups, as well as primary and secondary IRSA, are shown in Tables 2 and 3. No statistically significant differences were found in the distribution of genotype and allele frequencies of either SNP between IRSA patients and controls or patients with primary and secondary IRSA. Genotype frequencies did not deviate from Hardy–Weinberg equilibrium in any of the study groups (data not shown). Furthermore, we found no association between the MMP7 -181 A/G or MMP12 -82 A/G SNPs and IRSA under dominant, recessive, and codominant genetic models (Table 4). In addition, the combined analysis showed no statistically significant differences in the frequencies of any MMP7 -181 A/G and MMP12 -82 A/G genotype combinations between IRSA patients and controls (data not shown). According to the Database of single nucleotide polymorphisms (dbSNP; https://www.ncbi.nlm.nih.gov/snp), allele and genotype frequencies obtained in our population are consistent with the European population for both polymorphisms.

Table 2.

Genotype and allele frequencies of MMP7 -181 A/G and MMP12 -82 A/G SNPs in IRSA and control women

Patients (N = 149) n (%) Controls (N = 149) n (%) X 2 P value Primary IRSA (N = 98) n (%) Secondary IRSA (N = 51) n (%) X 2 P value
MMP7 -181 A/G
 Genotype
  AA 42 (28.2) 45 (30.2) 0.16 0.924 30 (30.6) 12 (23.5) 0.87 0.648
  AG 84 (56.4) 81 (54.4) 53 (54.1) 31 (60.8)
  GG 23 (15.4) 23 (15.4) 15 (15.3) 8 (15.7)
 Allele
  A 168 (56.4) 171 (57.4) 0.06 0.804 113 (57.6) 55 (53.9) 0.38 0.538
  G 130 (43.6) 127 (42.6) 83 (42.4) 47 (46.1)
MMP12 -82 A/G
 Genotype
  AA 116 (77.8) 114 (76.5) 4.07 0.130 75 (76.5) 41 (80.4) 0.29 0.590
  AG 33 (22.2) 31 (20.8) 23 (23.5) 10 (19.6)
  GG 0 (0.0) 4 (2.7) 0 (0.0) 0 (0.0)
 Allele
  A 265 (88.9) 259 (86.9) 0.57 0.451 173 (88.3) 92 (90.2) 0.25 0.614
  G 33 (11.1) 39 (13.1) 23 (11.7) 10 (9.8)

Table 3.

Genotype and allele frequencies of MMP7 -181 A/G and MMP12 -82 A/G SNPs in IRSA and control men

Patients (N = 147) n (%) Controls (N = 149) n (%) X 2 P value Primary IRSA (N = 97) n (%) Secondary IRSA (N = 50) n (%) X 2 P value
MMP7 -181 A/G
 Genotype
  AA 58 (39.5) 55 (36.9) 0.72 0.699 38 (39.2) 20 (40.0) 0.62 0.732
  AG 64 (43.5) 63 (42.3) 44 (45.4) 20 (40.0)
  GG 25 (17.0) 31 (20.8) 15 (15.4) 10 (20.0)
 Allele
  A 180 (61.2) 173 (58.1) 0.62 0.432 120 (61.9) 60 (60.0) 0.10 0.757
  G 114 (38.8) 125 (41.9) 74 (38.1) 40 (40.0)
MMP12 -82 A/G
 Genotype
  AA 114 (77.6) 113 (75.8) 0.12 0.728 72 (74.2) 42 (84.0) 1.81 0.178
  AG 33 (22.4) 36 (24.2) 25 (25.8) 8 (16.0)
  GG 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
 Allele
  A 261 (88.8) 262 (87.9) 0.11 0.746 169 (87.1) 92 (92.0) 1.58 0.209
  G 33 (11.2) 36 (12.1) 25 (12.9) 8 (8.0)

Table 4.

Association of MMP7 -181 A/G and MMP12-82 A/G SNPs with IRSA

Women Men
Patients vs. controls Primary vs. secondary IRSA Patients vs. controls Primary vs. secondary IRSA
Genetic model OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value OR (95% CI) P value
MMP7 -181 A/G
 Dominant AG + GG vs. AA 1.10 (0.67–1.82) 0.702 0.70 (0.32–1.52) 0.363 0.90 (0.56–1.44) 0.653 1.04 (0.52–2.08) 0.922
 Recessive GG vs. AA + AG 1.09 (0.58–2.04) 0.797 0.97 (0.38–2.47) 0.951 0.85 (0.47–1.53) 0.585 0.73 (0.30–1.77) 0.489
 Codominant GG vs. AA 1.07 (0.52–2.19) 0.850 0.75 (0.25–2.23) 0.604 0.77 (0.40–1.46) 0.414 0.79 (0.30–2.07) 0.631
 Codominant AG vs. AA 1.11 (0.66–1.87) 0.691 0.68 (0.31–1.53) 0.354 0.96 (0.58–1.60) 0.885 1.16 (0.54–2.47) 0.704
 Codominant AG vs. GG 1.04 (0.54–1.99) 0.913 0.91 (0.35–2.40) 0.851 1.26 (0.67–2.37) 0.474 1.47 (0.56–3.83) 0.434
 Allele G vs. A 1.04 (0.75–1.44) 0.804 0.86 (0.53–1.39) 0.538 0.95 (0.69–1.32) 0.773 0.93 (0.56–1.52) 0.757
MMP12 -82 A/G
 Dominant AG + GG vs. AA 0.93 (0.54–1.59) 0.782 1.26 (0.55–2.90) 0.591 0.91 (0.53–1.56) 0.728 1.82 (0.75–4.41) 0.182
 Recessive GG vs. AA + AG 0.11 (0.01–2.03) 0.137 0.52 (0.01–26.74) 0.747 1.01 (0.02–51.42) 0.995 0.52 (0.01–26.49) 0.743
 Codominant GG vs. AA 0.11 (0.01–2.05) 0.139 0.55 (0.01–28.21) 0.766 0.99 (0.02–50.39) 0.997 0.59 (0.01–30.09) 0.790
 Codominant AG vs. AA 1.05 (0.60–1.82) 0.873 1.26 (0.55–2.89) 0.591 0.91 (0.53–1.56) 0.728 1.82 (0.75–4.41) 0.182
 Codominant AG vs. GG 9.57 (0.50–185.08) 0.135 2.24 (0.04–120.61) 0.692 0.92 (0.02–47.57) 0.966 3.00 (0.06–163.16) 0.590
 Allele G vs. A 0.83 (0.50–1.36) 0.451 1.22 (0.56–2.68) 0.615 0.92 (0.56–1.52) 0.746 1.70 (0.74–3.92) 0.213

Finally, we found no differences in the distribution of haplotype frequencies between IRSA and control groups, as well as primary and secondary IRSA (Tables 5 and 6).

Table 5.

Haplotype frequencies of MMP7 -181 A/G and MMP12 -82 A/G SNPs and their association with IRSA in women

Haplotype Patients (N = 298) n (%) Controls (N = 298) n (%) X 2 P value OR (95% CI) P value Primary IRSA (N = 196) n (%) Secondary IRSA (N = 102) n (%) X 2 P value OR (95% CI) P value
MMP7 -181 MMP12 -82 2.13 0.545 0.46 0.927
A A 147 (49.4) 142 (47.5) 1.07 (0.77–1.47) 0.682 98 (49.9) 50 (48.6) 1.04 (0.64–1.68) 0.872
G A 118 (39.5) 117 (39.4) 1.04 (0.60–1.81) 0.887 75 (38.4) 42 (41.6) 0.88 (0.54–1.44) 0.625
A G 20 (6.7) 29 (9.9) 0.64 (0.35–1.19) 0.162 15 (7.7) 6 (5.4) 1.33 (0.50–3.53) 0.572
G G 13 (4.4) 10 (3.2) 1.33 (0.56–3.13) 0.516 8 (4.0) 4 (4.4) 1.04 (0.31–3.55) 0.947

Table 6.

Haplotype frequencies of MMP7 -181 A/G and MMP12 -82 A/G SNPs and their association with IRSA in men

Haplotype Patients (N = 294) n (%) Controls (N = 298) n (%) X 2 P value OR (95% CI) P value Primary IRSA (N = 194) n (%) Secondary IRSA (N = 100) n (%) X 2 P value OR (95% CI) P value
MMP7 -181 MMP12 -82 1.24 0.742 1.35 0.718
A A 158 (53.7) 153 (51.3) 1.10 (0.80–1.52) 0.559 103 (52.8) 57 (57.1) 0.85 (0.52–1.39) 0.524
G A 103 (35.1) 109 (36.6) 0.93 (0.67–1.31) 0.695 67 (34.4) 35 (34.7) 0.98 (0.59–1.62) 0.937
A G 22 (7.5) 20 (6.8) 1.12 (0.60–2.11) 0.715 18 (9.4) 6 (6.1) 1.60 (0.61–4.17) 0.334
G G 11 (3.7) 16 (5.3) 0.67 (0.31–1.48) 0.327 6 (3.3) 2 (2.1) 1.56 (0.31–7.89) 0.588

Discussion

In this study, we investigated, for the first time, the potential association between MMP7 -181 A/G and MMP12 -82 A/G functional SNPs and IRSA in Slovenian reproductive couples. We found no significant differences in any of the allele, genotype, or haplotype frequencies between patient and control groups, or association with IRSA under any genetic model. Therefore, our results suggest that MMP7 -181 A/G and MMP12 -82 A/G functional SNPs are not associated with IRSA.

The investigated genes were selected based on their confirmed roles in human pregnancy, whereas the SNPs were chosen according to their functionality and association with other disorders, including reproductive disorders.

Matrix metalloproteinase 7, also known as matrilysin or PUMP-1, has broad substrate specificity and is secreted mostly from the endometrial epithelium cells where attachment of the blastocyst occurs [37, 38]. In human placenta, MMP7 is secreted by cytotrophoblast and syncytiotrophoblast during early pregnancy; and by the third trimester only by cytotrophoblast [39]. Consequently, it has been suggested that MMP7 is important in the implantation process [40, 41]. Furthermore, MMP7 degrades soluble vascular endothelial growth factor receptor 1 (sVEGFR1) and increases the bioavailability of VEGF165, which promotes angiogenesis [42]. The G allele of the MMP7 -181 A/G SNP creates a putative binding site for a heat shock transcription factor, thereby increasing MMP7 gene promoter activity and transcription compared to the -181 A allele [34]. The G allele has been reported as a potential risk factor for several gynecological disorders, including endometriosis and adenomyosis [32], as well as endometrial [27], ovarian [26], and cervical cancers [28]. Moreover, the presence of the G allele has been associated with increased levels of malondialdehyde, a marker of lipid peroxidation, in severe preeclampsia [33]. Furthermore, the G allele has been associated with different types of extra-genital cancers [29, 30].

Matrix metalloproteinase 12 or macrophage elastase is also expressed by both the endometrium and trophoblast. Major sources of MMP12 are uterine natural killer cells and macrophages [43], interstitial and endovascular trophoblasts, as well as vascular smooth muscle cells [44]. The MMP12 is a key mediator of elastolysis and contributes to the remodeling of spiral arteries. Expression of the MMP12 gene was found to be upregulated in deciduas of women with IRSA compared to controls [12]. The A allele of the MMP12 -82 A/G SNP enhances the binding of the transcription factor activator protein 1, increasing promoter activity [45]. It has been suggested that the G allele is associated with epithelial ovarian carcinoma [46], whereas the AA genotype possibly contributes to a higher risk of disseminated colorectal carcinoma, chronic obstructive pulmonary disease, and systemic sclerosis [31, 35, 36].

The limitations of our study might be a relatively small sample size and the fact that genotyping was not performed on spontaneously aborted conceptuses. However, this study also has several strengths. For example, statistical power was sufficient and the selection criteria for patients and controls were strict. Moreover, considering that male genome has an inevitable role in reproductive success [47, 48], our study included male partners of IRSA women.

In conclusion, we found no evidence to support the association of MMP7 -181 A/G and MMP12 -82 A/G SNPs with IRSA in Slovenian population. Additional research is needed on a larger group of IRSA couples and different populations to detect smaller differences in allele frequency between the two groups and establish the possible role of MMP7 -181 A/G and MMP12 -82 A/G SNPs in IRSA.

Acknowledgements

This study was supported by research grants “Genetic factors in the etiology of idiopathic recurrent spontaneous abortion” (University of Rijeka, Croatia, number 13.06.1.3.32) and “Gynecology and Reproduction: Genomics and Stem Cells” (Slovenia, number P3―0326).

Compliance with ethical standards

Ethical approval

All procedures involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Conflict of interest

The authors declare that they have no conflicts of interest.

Informed consent

Written informed consent was obtained from all individual participants included in the study. The study was approved by Slovenian and Croatian National Ethics’ Committees and was performed in accordance with the ethical standards as described in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Studies with animals

This article does not contain any studies with animals performed by any of the authors.

Footnotes

Capsule We found no evidence to support the association between IRSA and MMP7 -181 A/G and MMP12 -82 A/G SNPs in Slovenian reproductive couples.

References

  • 1.Jauniaux E, Farquharson RG, Christiansen OB, Exalto N. Evidence-based guidelines for the investigation and medical treatment of recurrent miscarriage. Hum Reprod. 2006;21:2216–22. doi: 10.1093/humrep/del150. [DOI] [PubMed] [Google Scholar]
  • 2.Heuser C, Dalton J, Macpherson C, Branch DW, Porter TF, Silver RM. Idiopathic recurrent pregnancy loss recurs at similar gestational ages. Am J Obstet Gynecol. 2010;203:343.e1-5. [DOI] [PubMed]
  • 3.Ticconi C, Giuliani E, Sorge R, Patrizi L, Piccione E, Pietropolli A. Gestational age of pregnancy loss in women with unexplained recurrent miscarriage. J Obstet Gynaecol Res. 2016;42:239–45. doi: 10.1111/jog.12903. [DOI] [PubMed] [Google Scholar]
  • 4.Achache H, Revel A. Endometrial receptivity markers, the journey to successful embryo implantation. Hum Reprod Update. 2006;12:731–46. doi: 10.1093/humupd/dml004. [DOI] [PubMed] [Google Scholar]
  • 5.Díaz-Gimeno P, Ruíz-Alonso M, Blesa D, Simón C. Transcriptomics of the human endometrium. Int J Dev Biol. 2014;58:127–37. doi: 10.1387/ijdb.130340pd. [DOI] [PubMed] [Google Scholar]
  • 6.Houshdaran S, Zelenko Z, Irwin JC, Giudice LC. Human endometrial DNA methylome is cycle-dependent and is associated with gene expression regulation. Mol Endocrinol. 2014;28:1118–35. doi: 10.1210/me.2013-1340. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Ruiz-Alonso M, Blesa D, Simón C. The genomics of the human endometrium. Biochim Biophys Acta. 2012;1822:1931–42. doi: 10.1016/j.bbadis.2012.05.004. [DOI] [PubMed] [Google Scholar]
  • 8.Maslova MA, Smol’nikova VY, Savilova AM, Burmenskaya OV, Bystritskii AA, Tabolova VK, et al. Profiles of mRNA expression for genes involved in implantation, early and middle phases of secretion stage in human endometrium. Bull Exp Biol Med. 2015;158:781–4. doi: 10.1007/s10517-015-2861-5. [DOI] [PubMed] [Google Scholar]
  • 9.Othman R, Omar MH, Shan LP, Shafiee MN, Jamal R, Mokhtar NM. Microarray profiling of secretory-phase endometrium from patients with recurrent miscarriage. Reprod Biol. 2012;12:183–99. doi: 10.1016/S1642-431X(12)60085-0. [DOI] [PubMed] [Google Scholar]
  • 10.Jokimaa V, Oksjoki S, Kujari H, Vuorio E, Anttila L. Altered expression of genes involved in the production and degradation of endometrial extracellular matrix in patients with unexplained infertility and recurrent miscarriages. Mol Hum Reprod. 2002;8:1111–6. doi: 10.1093/molehr/8.12.1111. [DOI] [PubMed] [Google Scholar]
  • 11.Lee J, Oh J, Choi E, Park I, Han C, Kim DH, et al. Differentially expressed genes implicated in unexplained recurrent spontaneous abortion. Int J Biochem Cell Biol. 2007;39:2265–77. doi: 10.1016/j.biocel.2007.06.012. [DOI] [PubMed] [Google Scholar]
  • 12.Krieg SA, Fan X, Hong Y, Sang QX, Giaccia A, Westphal LM, et al. Global alteration in gene expression profiles of deciduas from women with idiopathic recurrent pregnancy loss. Mol Hum Reprod. 2012;18:442–50. doi: 10.1093/molehr/gas017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Cartwright JE, Fraser R, Leslie K, Wallace AE, James JL. Remodelling at the maternal-fetal interface: relevance to human pregnancy disorders. Reproduction. 2010;140:803–13. doi: 10.1530/REP-10-0294. [DOI] [PubMed] [Google Scholar]
  • 14.Jackson BC, Nebert DW, Vasiliou V. Update of human and mouse matrix metalloproteinase families. Hum Genomics. 2010;4:194–201. doi: 10.1186/1479-7364-4-3-194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Cohen M, Meisser A, Bischof P. Metalloproteinases and human placental invasiveness. Placenta. 2006;27:783–93. doi: 10.1016/j.placenta.2005.08.006. [DOI] [PubMed] [Google Scholar]
  • 16.Anacker J, Segerer SE, Hagemann C, Feix S, Kapp M, Bausch R, et al. Human decidua and invasive trophoblasts are rich sources of nearly all human matrix metalloproteinases. Mol Hum Reprod. 2011;17:637–52. doi: 10.1093/molehr/gar033. [DOI] [PubMed] [Google Scholar]
  • 17.Baek KH, Choi BC, Lee JH, Choi HK, Lee SH, Kim JW, et al. Comparison of gene expression at the feto-maternal interface between normal and recurrent pregnancy loss patients. Reprod Fertil Dev. 2002;14:235–40. doi: 10.1071/RD02008. [DOI] [PubMed] [Google Scholar]
  • 18.Baek KH. Aberrant gene expression associated with recurrent pregnancy loss. Mol Hum Reprod. 2004;10:291–7. doi: 10.1093/molehr/gah049. [DOI] [PubMed] [Google Scholar]
  • 19.Inagaki N, Stern C, McBain J, Lopata A, Kornman L, Wilkinson D. Analysis of intra-uterine cytokine concentration and matrix-metalloproteinase activity in women with recurrent failed embryo transfer. Hum Reprod. 2003;18:608–15. doi: 10.1093/humrep/deg139. [DOI] [PubMed] [Google Scholar]
  • 20.Skrzypczak J, Wirstlein P, Mikolajczyk M. Could the defects in the endometrial extracellular matrix during the implantation be a cause for impaired fertility? Am J Reprod Immunol. 2007;57:40–8. doi: 10.1111/j.1600-0897.2006.00443.x. [DOI] [PubMed] [Google Scholar]
  • 21.Banerjee P, Jana SK, Pasricha P, Ghosh S, Chakravarty B, Chaudhury K. Proinflammatory cytokines induced altered expression of cyclooxygenase-2 gene results in unreceptive endometrium in women with idiopathic recurrent spontaneous miscarriage. Fertil Steril. 2013;99:179–87. doi: 10.1016/j.fertnstert.2012.08.034. [DOI] [PubMed] [Google Scholar]
  • 22.Kuznetsova AV, Paukov VS, Voloshchuk IN, Demidova EM. Changes in the components of the extracellular matrix and its regulators in the endometrium of women with habitual abortion. Arkh Patol. 2002;64:18–22. [PubMed] [Google Scholar]
  • 23.Anumba DO, El Gelany S, Elliott SL, Li TC. Circulating levels of matrix proteases and their inhibitors in pregnant women with and without a history of recurrent pregnancy loss. Reprod Biol Endocrinol. 2010;8:62. doi: 10.1186/1477-7827-8-62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Choi HK, Choi BC, Lee SH, Kim JW, Cha KY, Baek KH. Expression of angiogenesis-and apoptosis-related genes in chorionic villi derived from recurrent pregnancy loss patients. Mol Reprod Dev. 2003;66:24–31. doi: 10.1002/mrd.10331. [DOI] [PubMed] [Google Scholar]
  • 25.Pereza N, Ostojić S, Volk M, Kapović M, Peterlin B. Matrix metalloproteinases 1, 2, 3 and 9 functional single-nucleotide polymorphisms in idiopathic recurrent spontaneous abortion. Reprod Biomed Online. 2012;24:567–75. doi: 10.1016/j.rbmo.2012.01.008. [DOI] [PubMed] [Google Scholar]
  • 26.Li Y, Jin X, Kang S, Wang Y, Du H, Zhang J, et al. Polymorphisms in the promoter regions of the matrix metalloproteinases-1, -3, -7, and -9 and the risk of epithelial ovarian cancer in China. Gynecol Oncol. 2006;101:92–6. doi: 10.1016/j.ygyno.2005.09.058. [DOI] [PubMed] [Google Scholar]
  • 27.Yi YC, Chou PT, Chen LY, Kuo WH, Ho ES, Han CP, et al. Matrix metalloproteinase-7 (MMP-7) polymorphism is a risk factor for endometrial cancer susceptibility. Clin Chem Lab Med. 2010;48:337–44. doi: 10.1515/CCLM.2010.082. [DOI] [PubMed] [Google Scholar]
  • 28.Singh H, Jain M, Mittal B. MMP-7 (−181A>G) promoter polymorphisms and risk for cervical cancer. Gynecol Oncol. 2008;110:71–5. doi: 10.1016/j.ygyno.2008.03.007. [DOI] [PubMed] [Google Scholar]
  • 29.Zhang J, Jin X, Fang S, Wang R, Li Y, Wang N, et al. The functional polymorphism in the matrix metalloproteinase-7 promoter increases susceptibility to esophageal squamous cell carcinoma, gastric cardiac adenocarcinoma and non-small cell lung carcinoma. Carcinogenesis. 2005;26:1748–53. doi: 10.1093/carcin/bgi144. [DOI] [PubMed] [Google Scholar]
  • 30.Kesh K, Subramanian L, Ghosh N, Gupta V, Gupta A, Bhattacharya S, et al. Association of MMP7–181A→G Promoter Polymorphism with Gastric Cancer Risk: Influence of nicotine in differential allele-specific transcription via increased phosphorylation of cAMP-response element-binding protein (CREB) J Biol Chem. 2015;290:14391–406. doi: 10.1074/jbc.M114.630129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.VAN Nguyen S, Skarstedt M, Löfgren S, Zar N, Andersson RE, Lindh M, et al. Gene polymorphism of matrix metalloproteinase-12 and -13 and association with colorectal cancer in Swedish patients. Anticancer Res. 2013;33:3247–50. [PubMed] [Google Scholar]
  • 32.Shan K, Lian-Fu Z, Hui D, Wei G, Na W, Xia J, et al. Polymorphisms in the promoter regions of the matrix metalloproteinases-7, -9 and the risk of endometriosis and adenomyosis in China. Mol Hum Reprod. 2006;12:35–9. doi: 10.1093/molehr/gal002. [DOI] [PubMed] [Google Scholar]
  • 33.Rahimi Z, Kazemian L, Malek-Khosravi S, Najafi F, Rahimi Z. Matrix metalloproteinase-7 A-181G and its interaction with matrix metalloproteinase-9C-1562T polymorphism in preeclamptic patients: association with malondialdehyde level and severe preeclampsia. Arch Gynecol Obstet. 2015;291:45–51. doi: 10.1007/s00404-014-3376-4. [DOI] [PubMed] [Google Scholar]
  • 34.Mohammadi F, Rahimi Z, Rahimi Z. The association between matrix metalloproteinase-7 A-181G polymorphism and the risk of relapsing-remitting multiple sclerosis in Iranian Kurdish patients from Kermanshah. Avicenna J Med Biochem. 2015;3:e25084.
  • 35.Mogulkoc U, Coskunpinar E, Aynaci E, Cağlar E, Ortakoylu MG, Ozkan G, et al. Is MMP-7 gene polymorphism a possible risk factor for chronic obstructive pulmonary disease in Turkish patients. Genet Test Mol Biomarkers. 2012;16:519–23. doi: 10.1089/gtmb.2011.0271. [DOI] [PubMed] [Google Scholar]
  • 36.Manetti M, Ibba-Manneschi L, Fatini C, Guiducci S, Cuomo G, Bonino C, et al. Association of a functional polymorphism in the matrix metalloproteinase-12 promoter region with systemic sclerosis in an Italian population. J Rheumatol. 2010;37:1852–7. doi: 10.3899/jrheum.100237. [DOI] [PubMed] [Google Scholar]
  • 37.Rodgers WH, Osteen KG, Matrisian LM, Navre M, Giudice LC, Gorstein F. Expression and localization of matrilysin, a matrix metalloproteinase, in human endometrium during the reproductive cycle. Am J Obstet Gynecol. 1993;168:253–60. doi: 10.1016/S0002-9378(12)90922-9. [DOI] [PubMed] [Google Scholar]
  • 38.Zhang X, Nothnick WB. The role and regulation of the uterine matrix metalloproteinase system in menstruating and non-menstruating species. Front Biosci. 2005;10:353–66. doi: 10.2741/1533. [DOI] [PubMed] [Google Scholar]
  • 39.Vettraino IM, Roby J, Tolley T, Parks WC. Collagenase-I, stromelysin-I, and matrilysin are expressed within the placenta during multiple stages of human pregnancy. Placenta. 1996;17:557–63. doi: 10.1016/S0143-4004(96)80072-5. [DOI] [PubMed] [Google Scholar]
  • 40.Zhang S, Lin H, Kong S, Wang S, Wang H, Wang H, et al. Physiological and molecular determinants of embryo implantation. Mol Aspects Med. 2013;34:939–80. doi: 10.1016/j.mam.2012.12.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Wilson CL, Matrisian LM. Matrilysin: an epithelial matrix metalloproteinase with potentially novel functions. Int J Biochem Cell Biol. 1996;28:123–36. doi: 10.1016/1357-2725(95)00121-2. [DOI] [PubMed] [Google Scholar]
  • 42.Ito TK, Ishii G, Saito S, Yano K, Hoshino A, Suzuki T, et al. Degradation of soluble VEGF receptor-1 by MMP-7 allows VEGF access to endothelial cells. Blood. 2009;113:2363–9. doi: 10.1182/blood-2008-08-172742. [DOI] [PubMed] [Google Scholar]
  • 43.Smith SD, Dunk CE, Aplin JD, Harris LK, Jones RL. Evidence for immune cell involvement in decidual spiral arteriole remodeling in early human pregnancy. Am J Pathol. 2009;174:1959–71. doi: 10.2353/ajpath.2009.080995. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Harris LK, Smith SD, Keogh RJ, Jones RL, Baker PN, Knöfler M, et al. Trophoblast- and vascular smooth muscle cell-derived MMP-12 mediates elastolysis during uterine spiral artery remodeling. Am J Pathol. 2010;177:2103–15. doi: 10.2353/ajpath.2010.100182. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Jormsjö S, Ye S, Moritz J, Walter DH, Dimmeler S, Zeiher AM, et al. Allele-specific regulation of matrix metalloproteinase-12 gene activity is associated with coronary artery luminal dimensions in diabetic patients with manifest coronary artery disease. Circ Res. 2000;86:998–1003. doi: 10.1161/01.RES.86.9.998. [DOI] [PubMed] [Google Scholar]
  • 46.Chen SS, Song J, Tu XY, Zhao JH, Ye XQ. The association between MMP-12 82 A/G polymorphism and susceptibility to various malignant tumors: a meta-analysis. Int J Clin Exp Med. 2015;8:10845–54. [PMC free article] [PubMed] [Google Scholar]
  • 47.Esplin MS, Fausett MB, Fraser A, Kerber R, Mineau G, Carrillo J, et al. Paternal and maternal components of the predisposition to preeclampsia. N Engl J Med. 2001;344:867–72. doi: 10.1056/NEJM200103223441201. [DOI] [PubMed] [Google Scholar]
  • 48.Haig D. Genetic conflicts in human pregnancy. Q Rev Biol. 1993;68:495–532. doi: 10.1086/418300. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Assisted Reproduction and Genetics are provided here courtesy of Springer Science+Business Media, LLC

RESOURCES