An association of Matrix Metalloproteinases-1/3 (MMP-1/3) rs1799750/rs3025058 polymorphism with increased risk of rotator cuff tear (RCT) has been reported in a Brazilian population. However, this significant association has not been confirmed in the Chinese population. Genotyping was conducted by polymerase chain reaction (PCR)-restriction fragment length polymorphism and direct sequencing. Our results demonstrated that individuals with the TT genotype had a significantly higher risk of RCT compared with those with the CC genotype. The increased risk of RCT progression was associated with the 2G allele of the rs1799750 polymorphism. No significant association was observed for genotypic and allelic frequencies of the rs3025058 polymorphism. A significant association of the MMP-1 rs1799750 polymorphism was observed with smokers, drinkers and people aged ≥60 years and non-diabetic people. Additionally, the MMP-1 rs1799750 polymorphism was associated with pre-operative stiffness in RCT patients. In conclusion, a significant correlation was identified between the MMP-1 rs1799750 polymorphism and RCT. The MMP-1 rs1799750 polymorphism might be considered as a biomarker of genetically high-risk RCT, helping to clarify the mechanism of RCT.

Rotator cuff tear (RCT) is a common injury among the elderly and it is characterized by pain, activity limitation and sleep disturbance [1]. These patients require consultations, physiotherapy, radiological examinations and surgery, leading to a considerable economic burden [2]. However, the etiology of RCT is poorly understood. There is evidence that patient’s age, tear size and tendon conformation are associated with the development of RCT [3,4]. Additionally, genetic factors play an important role in modifying an individual’s risk of RCT.

A normal tendon consists mainly of collagen fibrils [5]. Increased expression of type I and type III collagens in the ruptured tendon of a rotator cuff has been previously reported [6]. Increased expression of some extracellular matrix (ECM) proteins was observed in injured tendons [7]. Matrix metalloproteinases (MMPs) are a large group of proteolytic enzymes responsible for tissue remodeling and ECM degradation [8]. Increased expression of MMPs 1 and 9 as well as decreased MMP-3 expression is detected in torn RCT tissue [9]. MMP-1 is a protease that breaks down type I collagen fibers [10]. MMP-3 is involved in the degradation of various collagens and regulation and activation of MMPs [11].

The MMP-1 rs1799750 (1G>2G) and MMP-3 rs3025058 (6A>5A) polymorphisms, which are located in the promoter region of the MMP gene, are related to the expression and activity of these enzymes [12]. An association of rs1799750/rs3025058 polymorphism with increased risk of RCT has been reported in a Brazilian population [13]. However, this significant association has not been confirmed in the Chinese population. Therefore, this hospital-based case–control study was performed to investigate the role of rs1799750/rs3025058 polymorphisms in the risk of RCT.

Study subjects

In the present study, 150 patients with RCT and 150 healthy controls were recruited from the Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, the Second Affiliated Hospital of Jiaxing University and the Second Affiliated Hospital of Zhejiang University School of Medicine in China between September 2014 and July 2018. Patients with large to massive RCT in one or both shoulders documented by magnetic resonance imaging were included in the study, while patients with tendinopathy, calcifying tendinitis or inflammatory disease were excluded. All control individuals had intact supraspinatus, infraspinatus and subscapularis tendons in both shoulders. Individuals of the control group were selected among the ones receiving a routine health examination and without family history of RCT. Exclusion criteria for controls were a history of humeral fracture and shoulder treatment in the past 2 years. A self-designed questionnaire was used to collect demographic and clinical characteristics (age, gender, smoking habits, hypertension, tendinopathies in other joints and existence of relatives who previously had treatment for RCT) of RCT cases and control subjects.

The present study was approved by the Ethics Committees of the three hospitals from which participants were recruited. All subjects provided written informed consent prior to participation in the study.

Isolation of DNA and genotyping

Genomic DNA was isolated from whole blood using the QIAamp DNA Blood Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. The concentration and purity of the extracted DNA were estimated by the measurement of the optical density at 260/280 nm. Genotyping was performed by polymerase chain reaction (PCR) and direct sequencing. The primers were designed using Primer-BLAST and were synthesized commercially by GenScript Inc. (Nanjing, China). The primers used for the present study were as follows: Forward: 5′-TCGTGAGAATGTCTTCCCATT-3′, Reverse: 5′-TCTTGGATTGATTTGAGATAAGTGAAATC-3′ for MMP-1 rs1799750 polymorphism; Forward: 5′-GGTTCTCCATTCCTTTGATGGGGGGAAAGA-3′, Reverse: 5′-CTTCCTGGAATTCACATCACTGCCACCACT-3′ for MMP-3 rs3025058 polymorphism. PCR amplification was performed in a 25-μl reaction volume containing 1 μl genomic DNA, 2 μl of 2.5 mM dNTPs, 2.5 μl of 10× Taq buffer, 1 μl each primer (10 mM), 0.125 μl Taq and ddH2O. The PCR amplification involved preliminary denaturation at 95°C for 5 min, followed by 33 cycles of 30 s at 94°C, 30 s at 55°C, 45 s at 72°C and one final cycle of 10 min at 72°C. The PCR products were separated by 2% agarose gel electrophoresis and visualized by Ethidium Bromide staining (Invitrogen, Grand Island, U.S.A.). The amplified DNA was sequenced by GenScript Inc. (Nanjing, China). A random selection of (3%) was used to validate the genotyping results in a blinded manner; the results were 100% concordant.

Statistical analyses

Statistical analysis was performed using the SAS software package (var. 9.1.3; SAS Institute, Cary, NC, U.S.A.). The demographic and clinical characteristics of study participants were evaluated using Student’s t test (for continuous variables) or a chi-squared test (for categorical variables). Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the association between MMP1/3 gene polymorphisms and risk of RCT by logistic regression analyses with adjustment for relevant significant variables under the allelic, recessive, dominant, homozygous and heterozygous models. Subgroup analyses were performed according to gender, smoking and drinking habits, age, individuals with/without hypertension, diabetes and thyroid disease. Departure from Hardy–Weinberg equilibrium (HWE) for MMP1/3 genotype distributions in controls was evaluated using a goodness-of-fit chi-squared test. P<0.05 was considered statistically significant.

Characteristics of the study population

The baseline characteristics of the study population are listed in Table 1. The average age of the patients was 52.25 years compared with 54.17 years of the controls, with no statistically significant difference between the two groups. No significant difference was found between the two groups with regard to gender, hypertension and thyroid disease, whereas a significant difference was observed in the distribution of smokers (P=0.005), drinkers (P=0.001) and individuals with diabetes (P=0.023). Details of the family history, tear size and pre-operative stiffness in RCT patients are also shown in Table 1.

Table 1
Patient demographics and risk factors in RCT
CharacteristicsCase (n=150)Control (n=150)P
Age 52.25 ± 10.67 54.17 ± 11.10 0.128 
Sex   0.166 
  Male 82 (54.7%) 70 (46.7%)  
  Female 68 (45.3%) 80 (53.3%)  
Smoking   0.005 
  Yes 71 (47.3%) 47 (31.3%)  
  No 79 (52.7%) 103 (68.7%)  
Alcohol   0.001 
  Yes 83 (55.3%) 53 (35.3%)  
  No 67 (44.7%) 97 (64.7%)  
Hypertension   0.699 
  Yes 43 (28.7%) 40 (26.7%)  
  No 107 (71.3%) 110 (73.3%)  
Diabetes   0.023 
  Yes 39 (26.0%) 23 (15.3%)  
  No 111 (74.0%) 127 (84.7%)  
Thyroid disease   0.828 
  Yes 11 (7.3%) 12 (8.0%)  
  No 139 (92.7%) 138 (92.0%)  
Family history    
  Yes 12 (8.0%)   
  No 138 (92.0%)   
Tear size    
  Small 78 (52.0%)   
  Medium 44 (29.3%)   
  Large 28 (18.7%)   
Pre-operative stiffness    
  Yes 73 (48.7%)   
  No 77 (51.3%)   
CharacteristicsCase (n=150)Control (n=150)P
Age 52.25 ± 10.67 54.17 ± 11.10 0.128 
Sex   0.166 
  Male 82 (54.7%) 70 (46.7%)  
  Female 68 (45.3%) 80 (53.3%)  
Smoking   0.005 
  Yes 71 (47.3%) 47 (31.3%)  
  No 79 (52.7%) 103 (68.7%)  
Alcohol   0.001 
  Yes 83 (55.3%) 53 (35.3%)  
  No 67 (44.7%) 97 (64.7%)  
Hypertension   0.699 
  Yes 43 (28.7%) 40 (26.7%)  
  No 107 (71.3%) 110 (73.3%)  
Diabetes   0.023 
  Yes 39 (26.0%) 23 (15.3%)  
  No 111 (74.0%) 127 (84.7%)  
Thyroid disease   0.828 
  Yes 11 (7.3%) 12 (8.0%)  
  No 139 (92.7%) 138 (92.0%)  
Family history    
  Yes 12 (8.0%)   
  No 138 (92.0%)   
Tear size    
  Small 78 (52.0%)   
  Medium 44 (29.3%)   
  Large 28 (18.7%)   
Pre-operative stiffness    
  Yes 73 (48.7%)   
  No 77 (51.3%)   

Quantitative analysis

As is shown in Table 2, all observed genotype frequencies for the two polymorphisms (rs1799750 and rs3025058) in both controls and patients conformed to HWE, suggesting that these subjects are representative of the total population. The 2G/2G genotype of the rs1799750 polymorphism was significantly associated with a 2.05-fold increased risk of RCT in comparison with 1G/1G (OR = 2.05, 95% CI = 1.06–3.97, P=0.033). Moreover, the MMP-1 rs1799750 polymorphism was significantly associated with the risk of RCT in the allelic model (P=0.032). The MMP-3 rs3025058 polymorphism was not significantly associated with the risk of RCT. These findings were also confirmed after adjusting for gender and age.

Table 2
Genotype frequencies of MMP1 and MMP3 gene polymorphisms in cases and controls
ModelsGenotypeCase (n, %)Control (n, %)OR (95% CI)P-value*OR (95% CI)*P-value
rs1799750        
Co-dominant 1G/1G 37 (24.8%) 50 (33.8%) 1.00 (reference) - 1.00 (reference) 
Heterozygote 1G/2G 74 (49.7%) 73 (49.3%) 1.37 (0.80–2.34) 0.248 1.33 (0.78–2.28) 0.295 
Homozygote 2G/2G 38 (25.5%) 25 (16.9%) 2.05 (1.06–3.97) 0.033 2.01 (1.03-3.89) 0.040 
Dominant 1G/1G 37 (24.8%) 50 (33.8%) 1.00 (reference) 1.00 (reference) 
 1G/2G+2G/2G 112 (75.2%) 98 (66.2%) 1.54 (0.93–2.56) 0.091 1.51 (0.91–2.50) 0.114 
Recessive 1G/1G+1G/2G 111 (74.5%) 123 (83.1%) 1.00 (reference) 1.00 (reference) 
 2G/2G 38 (25.5%) 25 (16.9%) 1.68 (0.96–2.97) 0.071 1.67 (0.95–2.95) 0.076 
Allele 1G 148 (49.7%) 173 (58.4%) 1.00 (reference) - 1.00 (reference) 
 2G 150 (50.3%) 123 (41.6%) 1.43 (1.03–1.97) 0.032 
rs3025058        
Co-dominant 6A/6A 96 (64.0%) 100 (66.7%) 1.00 (reference) 1.00 (reference) 
Heterozygote 5A/6A 48 (32.0%) 42 (28.0%) 1.19 (0.72–1.96) 0.494 1.15(0.69–1.90) 0.599 
Homozygote 5A/5A 6 (4.0%) 8 (5.3%) 0.78 (0.26–2.34) 0.659 0.79 (0.26–2.36) 0.666 
Dominant 6A/6A 96 (64.0%) 100 (66.7%) 1.00 (reference) 1.00 (reference) 
 5A/6A+5A/5A 54 (36.0%) 50 (33.3%) 1.13 (0.70–1.81) 0.628 1.09 (0.68–1.76) 0.731 
Recessive 6A/6A+5A/6A 144 (96.0%) 142 (94.7%) 1.00 (reference) 1.00 (reference) 
 5A/5A 6 (4.0%) 8 (5.3%) 0.74 (0.25–2.19) 0.585 0.75 (0.25–2.23) 0.609 
Allele 6A 240 (80.0%) 242 (80.7%) 1.00 (reference) 1.00 (reference) 
 5A 60 (20.0%) 58 (19.3%) 1.04 (0.70–1.56) 0.837 - - 
ModelsGenotypeCase (n, %)Control (n, %)OR (95% CI)P-value*OR (95% CI)*P-value
rs1799750        
Co-dominant 1G/1G 37 (24.8%) 50 (33.8%) 1.00 (reference) - 1.00 (reference) 
Heterozygote 1G/2G 74 (49.7%) 73 (49.3%) 1.37 (0.80–2.34) 0.248 1.33 (0.78–2.28) 0.295 
Homozygote 2G/2G 38 (25.5%) 25 (16.9%) 2.05 (1.06–3.97) 0.033 2.01 (1.03-3.89) 0.040 
Dominant 1G/1G 37 (24.8%) 50 (33.8%) 1.00 (reference) 1.00 (reference) 
 1G/2G+2G/2G 112 (75.2%) 98 (66.2%) 1.54 (0.93–2.56) 0.091 1.51 (0.91–2.50) 0.114 
Recessive 1G/1G+1G/2G 111 (74.5%) 123 (83.1%) 1.00 (reference) 1.00 (reference) 
 2G/2G 38 (25.5%) 25 (16.9%) 1.68 (0.96–2.97) 0.071 1.67 (0.95–2.95) 0.076 
Allele 1G 148 (49.7%) 173 (58.4%) 1.00 (reference) - 1.00 (reference) 
 2G 150 (50.3%) 123 (41.6%) 1.43 (1.03–1.97) 0.032 
rs3025058        
Co-dominant 6A/6A 96 (64.0%) 100 (66.7%) 1.00 (reference) 1.00 (reference) 
Heterozygote 5A/6A 48 (32.0%) 42 (28.0%) 1.19 (0.72–1.96) 0.494 1.15(0.69–1.90) 0.599 
Homozygote 5A/5A 6 (4.0%) 8 (5.3%) 0.78 (0.26–2.34) 0.659 0.79 (0.26–2.36) 0.666 
Dominant 6A/6A 96 (64.0%) 100 (66.7%) 1.00 (reference) 1.00 (reference) 
 5A/6A+5A/5A 54 (36.0%) 50 (33.3%) 1.13 (0.70–1.81) 0.628 1.09 (0.68–1.76) 0.731 
Recessive 6A/6A+5A/6A 144 (96.0%) 142 (94.7%) 1.00 (reference) 1.00 (reference) 
 5A/5A 6 (4.0%) 8 (5.3%) 0.74 (0.25–2.19) 0.585 0.75 (0.25–2.23) 0.609 
Allele 6A 240 (80.0%) 242 (80.7%) 1.00 (reference) 1.00 (reference) 
 5A 60 (20.0%) 58 (19.3%) 1.04 (0.70–1.56) 0.837 - - 

The genotyping was successful in 149 cases and 148 controls for rs1799750; the genotyping was successful in 150 cases and 150 controls for rs3025058. Bold values are statistically significant (P<0.05).

*

Adjusted for age and sex.

Stratified analyses were conducted according to gender, smoking and drinking habits, age, hypertension, diabetes and thyroid disease (Table 3). When the subjects were stratified according to gender and thyroid disease, no significant difference was found in the frequencies of genotypes and alleles for the rs1799750 polymorphism between the groups. This increased effect of the rs1799750 polymorphism was also evident in subgroups of smokers, drinkers, people aged ≥60 years and subjects with diabetes.

Table 3
Stratified analyses between rs1799750 polymorphisms and the risk of RCT
Variablers1799750 (case/control)1G/2G vs. 1G/1G2G/2G vs. 1G/1G2G/2G vs. 1G/1G +CT2G/2G +1G/2G vs. 1G/1G
1G/1G1G/2G2G/2G
Sex        
  Male 17/22 43/34 21/13 1.64 (0.75–3.56); 0.214 2.09 (0.82–5.34); 0.123 1.51 (0.69–3.30); 0.303 1.76 (0.84–3.68); 0.132 
  Female 20/28 31/39 17/12 1.11 (0.53–2.34); 0.778 1.98 (0.78–5.06); 0.151 1.86 (0.82–4.24); 0.140 1.32 (0.66–2.64); 0.437 
Smoking        
  Yes 17/21 36/18 17/8 2.47 (1.05–5.80); 0.038 2.63 (0.91–7.55); 0.073 1.56 (0.61–3.99); 0.350 2.52 (1.14–5.57); 0.023 
  No 20/29 38/55 21/17 1.00 (0.50–2.03); 0.996 1.79 (0.76–4.22); 0.182 1.79 (0.87–3.68); 0.114 1.19 (0.61–2.31); 0.612 
Alcohol        
  Yes 20/22 43/26 20/5 1.82 (0.84–3.96); 0.131 4.40 (1.39–13.92); 0.012 3.05 (1.07–8.70); 0.037 2.24 (1.06–4.70); 0.034 
  No 17/28 31/47 18/20 1.09 (0.51–2.31); 0.830 1.48 (0.62–3.56); 0.379 1.41 (0.68–2.93); 0.362 1.21 (0.59–2.44); 0.606 
Age (years)        
  <60 31/31 52/49 27/16 1.06 (0.56–2.00); 0.854 1.69 (0.76–3.73); 0.196 1.63 (0.82–3.24); 0.168 1.22 (0.67–2.21); 0.521 
  ≥60 6/19 22/24 11/9 2.90 (0.98–8.59); 0.054 3.87 (1.09–13.81); 0.037 1.88 (0.69–5.11); 0.218 3.17 (1.12–8.93); 0.029 
Hypertension        
  Yes 9/13 27/22 7/5 1.77 (0.64–4.92); 0.271 2.02 (0.49–8.43); 0.334 1.36 (0.40–4.70); 0.626 1.82 (0.68–4.89); 0.236 
  No 28/37 47/51 31/20 1.22 (0.65–2.29); 0.541 2.05 (0.97–4.32); 0.060 1.82 (0.96–3.45); 0.067 1.45 (0.81–2.61); 0.213 
Diabetes        
  Yes 10/6 23/16 6/1 0.86 (0.26-2.85); 0.809 3.60 (0.35-37.60); 0.285 4.00 (0.45-35.54); 0.214 1.02 (0.32-3.32); 0.969 
  No 27/44 51/57 32/24 1.46 (0.79-2.68); 0.226 2.17 (1.06-4.44); 0.031 1.73 (0.94-3.17); 0.077 1.67 (0.95-2.95); 0.077 
Thyroid disease        
  Yes 1/2 6/9 4/1 1.33 (0.10-18.19); 0.829 8.00 (0.31-206.36); 0.210 6.29 (0.58-68.42); 0.131 2.00 (0.16-25.75); 0.595 
  No 35/48 68/64 34/24 1.42 (0.82–2.46); 0.215 1.89 (0.96–3.72); 0.066 1.53 (0.85–2.74); 0.158 1.55 (0.92–2.59); 0.099 
Variablers1799750 (case/control)1G/2G vs. 1G/1G2G/2G vs. 1G/1G2G/2G vs. 1G/1G +CT2G/2G +1G/2G vs. 1G/1G
1G/1G1G/2G2G/2G
Sex        
  Male 17/22 43/34 21/13 1.64 (0.75–3.56); 0.214 2.09 (0.82–5.34); 0.123 1.51 (0.69–3.30); 0.303 1.76 (0.84–3.68); 0.132 
  Female 20/28 31/39 17/12 1.11 (0.53–2.34); 0.778 1.98 (0.78–5.06); 0.151 1.86 (0.82–4.24); 0.140 1.32 (0.66–2.64); 0.437 
Smoking        
  Yes 17/21 36/18 17/8 2.47 (1.05–5.80); 0.038 2.63 (0.91–7.55); 0.073 1.56 (0.61–3.99); 0.350 2.52 (1.14–5.57); 0.023 
  No 20/29 38/55 21/17 1.00 (0.50–2.03); 0.996 1.79 (0.76–4.22); 0.182 1.79 (0.87–3.68); 0.114 1.19 (0.61–2.31); 0.612 
Alcohol        
  Yes 20/22 43/26 20/5 1.82 (0.84–3.96); 0.131 4.40 (1.39–13.92); 0.012 3.05 (1.07–8.70); 0.037 2.24 (1.06–4.70); 0.034 
  No 17/28 31/47 18/20 1.09 (0.51–2.31); 0.830 1.48 (0.62–3.56); 0.379 1.41 (0.68–2.93); 0.362 1.21 (0.59–2.44); 0.606 
Age (years)        
  <60 31/31 52/49 27/16 1.06 (0.56–2.00); 0.854 1.69 (0.76–3.73); 0.196 1.63 (0.82–3.24); 0.168 1.22 (0.67–2.21); 0.521 
  ≥60 6/19 22/24 11/9 2.90 (0.98–8.59); 0.054 3.87 (1.09–13.81); 0.037 1.88 (0.69–5.11); 0.218 3.17 (1.12–8.93); 0.029 
Hypertension        
  Yes 9/13 27/22 7/5 1.77 (0.64–4.92); 0.271 2.02 (0.49–8.43); 0.334 1.36 (0.40–4.70); 0.626 1.82 (0.68–4.89); 0.236 
  No 28/37 47/51 31/20 1.22 (0.65–2.29); 0.541 2.05 (0.97–4.32); 0.060 1.82 (0.96–3.45); 0.067 1.45 (0.81–2.61); 0.213 
Diabetes        
  Yes 10/6 23/16 6/1 0.86 (0.26-2.85); 0.809 3.60 (0.35-37.60); 0.285 4.00 (0.45-35.54); 0.214 1.02 (0.32-3.32); 0.969 
  No 27/44 51/57 32/24 1.46 (0.79-2.68); 0.226 2.17 (1.06-4.44); 0.031 1.73 (0.94-3.17); 0.077 1.67 (0.95-2.95); 0.077 
Thyroid disease        
  Yes 1/2 6/9 4/1 1.33 (0.10-18.19); 0.829 8.00 (0.31-206.36); 0.210 6.29 (0.58-68.42); 0.131 2.00 (0.16-25.75); 0.595 
  No 35/48 68/64 34/24 1.42 (0.82–2.46); 0.215 1.89 (0.96–3.72); 0.066 1.53 (0.85–2.74); 0.158 1.55 (0.92–2.59); 0.099 

Bold values are statistically significant (P<0.05).

Next a possible association was examined between MMP-1 rs1799750 polymorphism and clinicopathological features of patients (tear size, family history and pre-operative stiffness, Table 4). The CT or TT genotype was more frequent in patients with pre-operative stiffness compared with patients without pre-operative stiffness, indicating that this polymorphism was associated with pre-operative stiffness in RCT patients.

Table 4
The associations between MMP-1 rs1799750 polymorphism and clinical characteristics of RCT
CharacteristicsGenotype distributions
rs1799750CCCTTTCT+TT
Tear size     
  Large/Medium 6/10 16/18 6/16 22/34 
  OR (95%CI); P-value 1.0 (reference) 1.48(0.44–5.00); 0.525 0.63(0.16–2.49); 0.503 1.08 (0.34–3.39); 0.897 
Tear size     
  Large/Small 6/21 16/40 6/16 22/56 
  OR (95% CI; P-value 1.0 (reference) 1.40 (0.48–4.11); 0.539 1.31 (0.36–4.84); 0.683 1.38 (0.49–3.86); 0.545 
Family history     
  Yes/No 3/34 6/68 3/35 9/103 
  OR (95% CI); P-value 1.0 (reference) 1.00 (0.24–4.25); 1.000 0.97 (0.18–5.15); 0.973 0.99 (0.25–3.87); 0.989 
Pre-operative stiffness     
  Yes/No 12/25 39/35 22/16 61/51 
  OR (95% CI); P-value 1.0 (reference) 2.32 (1.02–5.30); 0.043 2.87 (1.12–7.35); 0.027 2.49 (1.14–5.45); 0.020 
CharacteristicsGenotype distributions
rs1799750CCCTTTCT+TT
Tear size     
  Large/Medium 6/10 16/18 6/16 22/34 
  OR (95%CI); P-value 1.0 (reference) 1.48(0.44–5.00); 0.525 0.63(0.16–2.49); 0.503 1.08 (0.34–3.39); 0.897 
Tear size     
  Large/Small 6/21 16/40 6/16 22/56 
  OR (95% CI; P-value 1.0 (reference) 1.40 (0.48–4.11); 0.539 1.31 (0.36–4.84); 0.683 1.38 (0.49–3.86); 0.545 
Family history     
  Yes/No 3/34 6/68 3/35 9/103 
  OR (95% CI); P-value 1.0 (reference) 1.00 (0.24–4.25); 1.000 0.97 (0.18–5.15); 0.973 0.99 (0.25–3.87); 0.989 
Pre-operative stiffness     
  Yes/No 12/25 39/35 22/16 61/51 
  OR (95% CI); P-value 1.0 (reference) 2.32 (1.02–5.30); 0.043 2.87 (1.12–7.35); 0.027 2.49 (1.14–5.45); 0.020 

Bold values are statistically significant (P<0.05).

The results of the present study showed that the MMP-1 rs1799750 polymorphism conferred susceptibility to RCT, while no significant association was observed with the rs3025058 polymorphism. Subgroup analysis indicated that the MMP-1 rs1799750 polymorphism was associated with an increased risk of RCT among smokers, drinkers, age ≥60 years and subjects without diabetes. Additionally, this polymorphism was associated with pre-operative stiffness in RCT patients.

The MMP-1 rs1799750 polymorphism has been investigated in relation to various diseases, such as ovarian cancer [14], lung cancer [15], glaucoma [16] and osteoarthritis [17]. However, few studies investigated a potential association with the susceptibility to RCT. The frequency of MMP-1 and MMP-9 were significantly more pronounced in the patients with RCT [17]. Up-regulation of MMP-1 and MMP-9 was highly correlated with the failure in the healing of RCT [18]. Therefore, the aim of this research was to focus on the role of MMP-1 rs17799750 polymorphism in the risk of RCT. In a study of 64 patients with full-thickness RCT and 64 asymptomatic control subjects in a Brazilian population, Assuncao et al. [13] found that MMP-1 rs7799750 polymorphism was associated with the risk of RCT in homozygous, heterozygous and allelic models; the results of our study are consistent with this report despite performed in a different population. Furthermore, the significant association appeared strong among smokers, drinkers, people aged ≥60 years and subjects without diabetes. Therefore, our hypothesis was that the rs1799750 polymorphism is involved in the development of RCT by regulating the activity and production of MMP-1.

Similarly, the association between the MMP3 rs3025058 polymorphism and disease risk has been widely investigated for conditions such as ischemic stroke [19], coronary disease [20], chronic obstructive pulmonary disease [21] and abdominal aortic aneurysm [22]. Only one study evaluated the role of MMP3 rs3025058 polymorphism in the risk of RCT [13] and it is again the one of Assuncao et al. [13] in a Brazilian (Caucasian) population. Their case–control study involving 64 cases and 64 controls showed that the 5A/5A genotype or 5A allele was associated with an increased risk of RCT. However, in our study, no significant association was observed in the eastern Chinese (Asian) population (150 cases and 150 controls), demonstrating the importance of validating the role of this polymorphism in other races. Three reasons might account for the conflicting results between Asians and Caucasians. First, a difference exists in allele frequency of the MMP-3 rs3025058 polymorphism among these ethnic groups. Second, different genotyping methods and random errors might contribute to these discrepancies. Third, the sample size of the Caucasian population (64 cases and 64 controls) was not sufficient to reach a convincing conclusion in comparison with Asian populations.

Several potential limitations might influence our results. First, the lack of available original data prevented the adjustment for other covariates, such as diet and lifestyle. Second, we could not rule out the possibility of random discoveries due to the limited sample size. Third, since RCT is a multifactorial disease, single nucleotide polymorphisms have a limited impact. Fourth, the included controls might not represent the overall population of East China because this is a hospital-based case–control study. Thus, higher powered studies in a large population, as well as functional evaluation of the studied polymorphism are needed to confirm the findings of the present study.

Despite these limitations, our work demonstrated that MMP-1 rs1799750 polymorphism is a genetic contributor to the risk of RCT and can be used as a biomarker for early screening and treatment of RCT.

Conceived and designed the experiments: J.Z. and J.L. Performed the experiments: K.M., L.J. and X.Z. Analyzed the data: K.M., L.W. and Y.H. Contributed reagents/materials/analysis tools: Y.H. and N.X. Wrote the paper: K.M., J.Z. and J.L.

The authors declare that there are no competing interests associated with the manuscript.

This work was supported in part by the National Natural Science Foundation of China [grant number 81702179].

CI

confidence interval

ECM

extracellular matrix

HWE

Hardy–Weinberg equilibrium

MMP

matrix metalloproteinase

OR

odds ratio

PCR

polymerase chain reaction

RCT

rotator cuff tear

1.
Kannus
P.
and
Jozsa
L.
(
1991
)
Histopathological changes preceding spontaneous rupture of a tendon. A controlled study of 891 patients
.
J. Bone Joint Surg. Am.
73
,
1507
1525
[PubMed]
2.
Oh
L.S.
,
Wolf
B.R.
,
Hall
M.P.
,
Levy
B.A.
and
Marx
R.G.
(
2007
)
Indications for rotator cuff repair: a systematic review
.
Clin. Orthop. Relat. Res.
455
,
52
63
[PubMed]
3.
Bjornsson
H.C.
,
Norlin
R.
,
Johansson
K.
and
Adolfsson
L.E.
(
2011
)
The influence of age, delay of repair, and tendon involvement in acute rotator cuff tears: structural and clinical outcomes after repair of 42 shoulders
.
Acta Orthop.
82
,
187
192
[PubMed]
4.
Saraswat
M.K.
,
Styles-Tripp
F.
,
Beaupre
L.A.
,
Luciak-Corea
C.
,
Otto
D.
,
Lalani
A.
et al.
(
2015
)
Functional outcomes and health-related quality of life after surgical repair of full-thickness rotator cuff tears using a mini-open technique: a concise 10-year follow-up of a previous report
.
Am. J. Sports Med.
43
,
2794
2799
[PubMed]
5.
Blevins
F.T.
,
Djurasovic
M.
,
Flatow
E.L.
and
Vogel
K.G.
(
1997
)
Biology of the rotator cuff tendon
.
Orthop. Clin. North Am.
28
,
1
16
[PubMed]
6.
Shirachi
I.
,
Gotoh
M.
,
Mitsui
Y.
,
Yamada
T.
,
Nakama
K.
,
Kojima
K.
et al.
(
2011
)
Collagen production at the edge of ruptured rotator cuff tendon is correlated with postoperative cuff integrity
.
Arthroscopy
27
,
1173
1179
[PubMed]
7.
Xu
Y.
and
Murrell
G.A.
(
2008
)
The basic science of tendinopathy
.
Clin. Orthop. Relat. Res.
466
,
1528
1538
[PubMed]
8.
Mittal
R.
,
Patel
A.P.
,
Debs
L.H.
,
Nguyen
D.
,
Patel
K.
,
Grati
M.
et al.
(
2016
)
Intricate functions of matrix metalloproteinases in physiological and pathological conditions
.
J. Cell. Physiol.
231
,
2599
2621
[PubMed]
9.
Lakemeier
S.
,
Braun
J.
,
Efe
T.
,
Foelsch
C.
,
Archontidou-Aprin
E.
,
Fuchs-Winkelmann
S.
et al.
(
2011
)
Expression of matrix metalloproteinases 1, 3, and 9 in differing extents of tendon retraction in the torn rotator cuff
.
Knee Surg. Sports Traumatol. Arthrosc.
19
,
1760
1765
[PubMed]
10.
Pardo
A.
and
Selman
M.
(
2005
)
MMP-1: the elder of the family
.
Int. J. Biochem. Cell Biol.
37
,
283
288
[PubMed]
11.
Garofalo
R.
,
Cesari
E.
,
Vinci
E.
and
Castagna
A.
(
2011
)
Role of metalloproteinases in rotator cuff tear
.
Sports Med. Arthrosc. Rev.
19
,
207
212
[PubMed]
12.
Millar
N.L.
,
Wei
A.Q.
,
Molloy
T.J.
,
Bonar
F.
and
Murrell
G.A.
(
2009
)
Cytokines and apoptosis in supraspinatus tendinopathy
.
J. Bone Joint Surg. Br.
91
,
417
424
[PubMed]
13.
Assuncao
J.H.
,
Godoy-Santos
A.L.
,
Dos Santos
M.
,
Malavolta
E.A.
,
Gracitelli
M.E.C.
and
Ferreira Neto
A.A.
(
2017
)
Matrix metalloproteases 1 and 3 promoter gene polymorphism is associated with rotator cuff tear
.
Clin. Orthop. Relat. Res.
475
,
1904
1910
[PubMed]
14.
Zhu
X.M.
and
Sun
W.F.
(
2017
)
Association between matrix metalloproteinases polymorphisms and ovarian cancer risk: a meta-analysis and systematic review
.
PLoS ONE
12
,
e0185456
[PubMed]
15.
Hu
J.
,
Pan
J.
and
Luo
Z.G.
(
2012
)
MMP1 rs1799750 single nucleotide polymorphism and lung cancer risk: a meta-analysis
.
Asian Pac. J. Cancer Prev.
13
,
5981
5984
[PubMed]
16.
He
M.
,
Wang
W.
,
Han
X.
and
Huang
W.
(
2017
)
Matrix metalloproteinase-1 rs1799750 polymorphism and glaucoma: a meta-analysis
.
Ophthal. Genet.
38
,
211
216
[PubMed]
17.
Peng
L.
,
Bin
J.
,
Ou
Y.C.
,
Zhu
L.X.
and
Lu
J.P.
(
2019
)
Lack of association between matrix metalloproteinase-1 gene rs1799750 polymorphism and osteoarthritis susceptibility: a meta-analysis
.
Biosci. Rep.
39
,
18.
Robertson
C.M.
,
Chen
C.T.
,
Shindle
M.K.
,
Cordasco
F.A.
,
Rodeo
S.A.
and
Warren
R.F.
(
2012
)
Failed healing of rotator cuff repair correlates with altered collagenase and gelatinase in supraspinatus and subscapularis tendons
.
Am. J. Sports Med.
40
,
1993
2001
[PubMed]
19.
Zhang
Q.W.
(
2018
)
Association of the matrix metalloproteinase-3 polymorphisms rs679620 and rs3025058 with ischemic stroke risk: a meta-analysis
.
Neuropsychiatr. Dis. Treat.
14
,
419
427
[PubMed]
20.
Koch
W.
,
de Waha
A.
,
Hoppmann
P.
,
Schomig
A.
and
Kastrati
A.
(
2010
)
Haplotypes and 5A/6A polymorphism of the matrix metalloproteinase-3 gene in coronary disease: case-control study and a meta-analysis
.
Atherosclerosis
208
,
171
176
[PubMed]
21.
Jiang
S.
,
Yang
Z.H.
,
Chen
Y.Y.
,
He
Z.
,
Zhou
Y.
,
Gao
Y.
et al.
(
2016
)
MMP-9 genetic polymorphism may confer susceptibility to COPD
.
Genet Mol. Res.
15
,
22.
Saratzis
A.
,
Bown
M.J.
,
Wild
B.
,
Nightingale
P.
,
Smith
J.
,
Johnson
C.
et al.
(
2015
)
Association between seven single nucleotide polymorphisms involved in inflammation and proteolysis and abdominal aortic aneurysm
.
J. Vasc. Surg.
61
,
1120
1128.e1121
[PubMed]
This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).