Abstract
Background/Aim: The studies about the roles of matrix metalloproteinases (MMPs) in pterygium diagnosis and/or prognosis are mainly based on their mRNA and protein levels, while the genomic roles of MMPs are seldom examined. The aim of this study was to investigate the contribution of MMP-9 genotypes to pterygium risk. Materials and Methods: MMP-9 rs3918242 was genotyped in 134 pterygium cases and 268 controls via polymerase chain reaction-restriction fragment length polymorphism. Results: The rs3918242 genotype percentages of CC, CT, and TT were 73.1, 25.4 and 1.5% among cases and 74.6, 23.1 and 2.3% among controls (p trend=0.7928). The odds ratios after adjusting for age and gender for CT and TT genotypes at rs3918242 were 1.08 and 0.92 (95%CI=0.66-1.73 and 0.45-2.89, p=0.6478 and 0.6389), respectively. In addition, allelic frequency analysis showed no significant difference in the distribution of allelic frequencies between the pterygium and control groups. Conclusion: The genotypes at MMP-9 rs3918242 play a minor role in determining personal susceptibility to pterygium.
Pterygium, the formation of fibro-vascular tissues that proliferate excessively and generate an abnormal wing-shaped growth, has similar characters to solid cancers (1). Mounting epidemiological studies have shown that there are various risk factors for pterygium, including heat, dust, particles in the atmosphere, immunological mechanisms, agents inducing extracellular matrix reorganization, growth factors, cytokines, and those affecting apoptosis (2-10). In addition, several case-control genotyping studies have demonstrated that inherited genomic variants may contribute to the determination of individual susceptibility to pterygium (11-13).
Extracellular matrix (ECM) remodeling including elastosis and Bowman's layer breakage can serve as typical characteristics of pterygium (14). These alterations may be attributed to the expression levels and activities of a group of enzymes, which are in charge of the degradation of ECM components. These enzymes are called matrix metalloproteinases (MMPs) or matrixins (15). In addition to cell proliferation, differentiation, and apoptosis, MMPs also play a critical role in several tumor-related behaviors, such as invasion, adhesion, dispersion, migration, angiogenesis and immune surveillance (16, 17). In literature, several polymorphic genotypes of MMPs have been associated with personal susceptibility to specific types of cancer (18-21). Among the MMPs, MMP-9 has been frequently found to be over-expressed in tumor tissues, breaking down basement membranes and the ECM during cancer invasion and metastasis (22). Interestingly, the expression of MMP-9 has also been found to be higher among pterygium tissues and fibroblasts compared to those of normal tissues (23), and closely correlated with the progression stages of pterygium (24). Among the single-nucleotide polymorphic sites in the promoter region of MMP-9, MMP-9 C-1562T (rs3918242) is the most frequently studied one. In literature, the genotypes of MMP-9 C-1562T (rs3918242) have been reported to serve as a practical genomic marker for cancer risk prediction of several types of cancer, such as gastric (25, 26), lung cancer (27), prostate cancer (28), and breast cancer (29). Therefore, the contribution of MMP-9 genotypes to pterygium, which has never been examined, has arisen our curiosity. We hypothesized that the variant genotypes at the promoter region of MMP-9 C-1562T (rs3918242) may affect the expression levels of MMP-9, and thus an individual's susceptibility to pterygium.
Materials and Methods
Collection of pterygium and control populations. The concepts, hypothesis and protocols of the current study have been approved by the Institutional Review Board of Changhua Christian Hospital and written informed consent has been obtained from one or both parents of all participants. Totally, 134 cases diagnosed with pterygium and 268 controls were recruited in this study. All participant have completed the questionnaire, and provided 5 ml of their peripheral blood samples for genotyping. The healthy controls were subjects aged 45 years or more without pterygium or any type of cancer. Basic characteristics of the participants are summarized and compared in Table I.
MMP-9 rs3918242 genotyping methodology. Genomic DNA was extracted within 12 h after receiving the blood, diluted and aliquoted for MMP-9 rs3918242 genotyping as a working stock at −20°C (12, 30). In the current study, the sequences of MMP-9 rs3918242 specific forward and reverse primers were 5’-TGGTCAACGTAGTGAAACCCCATCT-3’ and 5’-TCCAGCCCCAATTATCACACTTAT-3’, respectively. The PCR-based genotyping conditions for MMP-9 rs3918242 were: originally one cycle at 94°C for 5 min; followed by 35 cycles at 94°C for 30 s, 59°C for 30 s and 72°C for 30 s; and a terminal extension at 72°C for 10 min. After the PCR cycles, those MMP-9 rs3918242-containing DNA amplicons from each subject were digested with Sph I (New England Biolabs, Taipei, Taiwan) at 37oC overnight. Since the C- and T-allele DNA adducts are non-digestible and digestible to Sph I, respectively, the DNA adducts of MMP-9 rs3918242 CC, CT and TT genotypes are of 386 bp only, 386+320+66 multiple bps, and 320+66 bps, respectively. After enzyme digestion, all samples were immediately separated by 3.0% agarose gel electrophoresis. All the MMP-9 rs3918242 genotyping protocols were repeated independently and blindly at least twice, and the results were 100% concordant to each other. The overall success rate of the MMP-9 rs3918242 genotyping work was 100%. Furthermore, 5% of all the PCR products were randomly selected and sent for direct sequencing (Genomics BioSci & Tech Co). There was 100% concordance between the results of direct sequencing and PCR-RFLP.
Statistical analysis. Typical Pearson's Chi-square test without Yates' correction (when all numbers were equal to or larger than 5) and Fisher's exact test (when any number was less than 5) were used to compare the distribution of the gender, and of MMP-9 rs3918242 genotypic and allelic distributions between subgroup pairs such as pterygium and control groups. Also, the unpaired Student's t-test was used to compare the distribution of the ages between the pterygium and control groups. In addition, the associations between the MMP-9 rs3918242 polymorphisms and pterygium risk were estimated via calculating the odds ratios (ORs) as well as their corresponding 95% confidence intervals (CIs) from unconditional logistic regression analysis, with adjustment for possible confounding factors including age and gender when needed (Tables II and III). p-Values less than 0.05 indicated statistically significant differences between the compared subgroups.
Results
Distributions of ages and genders. The distributions of age and gender in the 134 pterygium patients and the 268 non-pterygium controls are shown in Table I. There were 78 males and 56 females in the pterygium group, aged between 48 to 89 years and the average age of these 134 pterygium patients was 64.4 years old. At the same time, 268 healthy participants were included into the control group, and matched according to gender, and age, so that the difference was less than 5 years. Since we originally matched the subjects according to age and gender in our research design, there was no significant difference between the two groups in the aspects of age or gender (both p>0.05) (Table I).
MMP-9 rs3918242 genotypes analysis. The results of the genotypic analysis of the MMP-9 rs3918242 among the pterygium cases and non-pterygium controls are presented in Table II. First, the distribution of MMP-9 rs3918242 among the controls fitted well with the Hardy-Weinberg Equation (p=0.6471). Second, the genotypic frequency distributions at MMP-9 rs3918242 were not statistically different between the pterygium and control groups (p for trend=0.7928) (Table II, top panel). In detail, the MMP-9 rs3918242 heterozygous CT and homozygous TT variant genotypes were both not associated with altered risk for pterygium compared with the wild-type CC genotype among the investigated population (p=0.6478 and 0.6389, adjusted OR=1.08 and 0.92, 95%CI=0.66-1.73 and 0.45-2.89, respectively; Table II, top panel). In the recessive model, the combination of the wild-type CC and heterozygous variant CT genotypes (CC+CT) at MMP-9 rs3918242 conferred an unaltered risk for pterygium compared with the TT genotype (p=0.6135) (Table II, middle panel). In the dominant model, the TT+CT carriers at MMP-9 rs3918242 conferred a slightly higher risk of pterygium compared to the CC genotype carriers (p=0.7474, aOR=1.0-5 and 95%CI=0.42-1.84) (Table II, bottom panel). Overall, the MMP-9 rs3918242 genotypes did not play a critical role in determining personal susceptibility to pterygium.
MMP-9 rs3918242 allelic frequencies analysis. Allelic frequency analysis of MMP-9 rs3918242 in relation to pterygium risk was then conducted to confirm the findings shown in Table II. The results are shown in Table III. Consistent with the findings shown in Table II, there was no significant difference in the distribution of allelic frequencies between the pterygium and control groups regarding MMP-9 rs3918242 (Table III). In detail, the adjusted OR for the subjects carrying the variant T allele at MMP-9 rs3918242 was 1.06 (95%CI=0.71-1.46, p=0.8855), compared to those carrying the wild-type C allele (Table III).
Distribution of age and gender of the 134 pterygium patients and the 268 non-pterygium controls.
Distributions of matrix metalloproteinase-9 rs3918242 genotypic frequencies among the pterygium patients and healthy controls.
Allelic frequencies for matrix metalloproteinase-9 rs3918242 polymorphisms among the pterygium patients and healthy controls.
Discussion
MMPs are proteinases in charge of the homeostasis of ECM components and partitions, and any imbalance in the ECM microenvironment may contribute to the initiation and progression of pterygium. Increased expression of MMP-1, MMP-2, MMP-3, MMP-7, MMP-8, and MMP-9 in pterygium tissues was reported in the early 2000s (15, 31-33). Furthermore, MMP-2 and MMP-9 expression is relatively lower in early-stage pterygium tissues and cultured fibroblasts than in advanced-stage pterygium tissues (24). In addition, Kim and his colleagues have reported that down-regulation of MMP-3 and MMP-13 can suppress the proliferation and migration of pterygium fibroblasts (34). These findings support the idea that MMPs play a critical role in the progression of pterygium. However, the contribution of MMP genotypes to the risk of pterygium remains unclear.
In literature, several polymorphic sites have been examined for their contributions to pterygium risk prediction. For instance, the 1G allele at MMP-1 -1607 (rs1799705) seems to serve as a protective marker for pterygium (13). However, the genotypes at MMP-7 A-181G are not associated with pterygium risk, and there is no polymorphic genotype for MMP7 C-153T among Taiwanese (12). Also, the genotypes at MMP-8 -799C/T, Val436Ala and Lys460Thr are not differentially distributed between the pterygium patient and healthy control groups (11). The positive association of MMP-1 rs1799750 genotypes with pterygium supports the idea that polymorphic variations in MMP-1 promoter region may influence personal susceptibility to pterygium via regulating MMP-1 mRNA and protein levels. This is consistent with similar findings in childhood leukemia (35) and gastric cancer (36). We also emphasize the genotypic roles of the tissue inhibitors of metalloproteinases (TIMPs), which have never been investigated in pterygium.
In conclusion, this is the first study that has provided evidence on the association of genotypes at MMP-9 with pterygium. Our results suggest that the variant genotypes of the rs3918242 at the promoter of MMP-9 confer a minor role in determining personal pterygium risk among Taiwanese. In the near future, the genotypes of other members of MMPs, such as MMP-2, -3, -13 (34), -10 (23), together with TIMPs (23), should be examined and their associations to pterygium should be revealed. Although the findings in the current study are negative, they should be validated in further studies in other populations.
Acknowledgements
The Authors are grateful to Yu-Chen Hsiau, Yu-Hsin Lin and Yi-Ru Huang for their excellent technical assistance. The great help from Dr. Hu, Dr. Chen, the nurses, and all participants including those who were not selected into the control group of the study are appreciated. This study was supported mainly by Chia-Yi Christian Hospital, Chia-Yi, Taiwan to Dr. Tsai (grant number: I108HA131). The funders had no role in study design, data collection, statistical analysis, or decision to publish or preparation of the manuscript.
Footnotes
Authors' Contributions
Research design: Tsai CB, Wang YC and Yin MC; patient and questionnaire summaries: Tsai CB and Hsia NY; experimental work: Wang YC, Yang JS and Hsu YM; statistical analysis: Wang ZH and Chang WS; article writing: Tsai CW and Bau DT; review and revision: Chang WS, Tsai CW and Bau DT.
Conflicts of Interest
All the Authors have declared no conflicts of interest regarding this study.
- Received June 11, 2020.
- Revision received July 2, 2020.
- Accepted July 3, 2020.
- Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved
