Correlation between vascular endothelial growth factor A gene polymorphisms and tendon and ligament injury risk: a systematic review and meta-analysis.

Eighty-six relevant papers were retrieved from major databases via strict implementation of the inclusion criteria. After excluding publications that were not case–control studies, duplicate publications, and other irrelevant literature, nine relevant papers were preliminarily screened; six papers (with 1061 individuals in the case group and 986 individuals in the control group) were finally included after careful reading of the full text. Six articles investigated rs699947, and four articles evaluated rs1570360 and rs2010963. The literature screening process and results are shown in Fig.  1 , and the basic characteristics of the included studies are shown in Table  1 [ 19 , 27 – 31 ]. The mode of injury and occupational status within the case group are presented in Table  2 , and Tables  3 , 4 and 5 show the detailed gene frequencies of VEGFA rs699947, rs1570360, and rs2010963 polymorphisms. Fig. 1 Flow diagram of literature searching Table 1 Main characteristics and quality score of studies included References Country Ethnicity Gender (F/M) Cases Controls NOS score N Age a Of cite Diagnosis Matching N Age a HWE Healthy Cięszczyk et al. [ 27 ] Poland Caucasian 115/257 229 26 ± 4 ACL Surgery Age and Sex 143 24.2 ± 4.1 HWE Yes 7 Shukla et al. [ 28 ] India–United Kingdom Indo-Pakistani 32/134 90 26.6 ± 6.2 ACL Radiology or Surgery Age and Sex 76 62.2 ± 5.7 HWE Yes 7 Rahim et al.[ 29 ] South Africa Caucasian SA 78/150 108 42.9 ± 13.6 Achilles Tendon WHO Age and Sex 120 37.3 ± 10.4 HWE Yes 6 United Kingdom UK 84/133 87 45.2 ± 14.4 130 41.6 ± 11.6 HWE Yes Rahim et al.[ 30 ] South Africa Colored 36/162 98 24.5 ± 7.5 ACL WHO Age and Sex 100 27.4 ± 6.7 HWE Yes 5 Rahim et al.[ 31 ] South Africa Caucasian 151/310 227 26.8 ± 11.0 ACL WHO Sex 234 29.3 ± 11.3 HWE Yes 6 Lulińska-Kuklik et al. [ 19 ] Poland Caucasian 149/263 222 F 25 ± 4 ACL Surgery Sex 190 F 29 ± 2 HWE Yes 7 M 26 ± 4 M 25 ± 2 F female, M male, NA not available, ACL anterior cruciate ligament, WHO World Health Organization diagnostic criteria, HWE Hardy–Weinberg equilibrium, a mean ± SD, NA not available Table 2 Profession and mode of injury in the case groups of included studies Group References Cięszczyk et al. [ 27 ] Shukla et al. [ 28 ] Rahim et al. [ 29 ] Rahim et al. [ 30 ] Rahim et al. [ 31 ] Lulińska-Kuklik et al. [ 19 ] Profession  Case Football player Athletes Patients with achilles tendinopathy Healthy people Healthy people Football player  Control Football player Athletes Healthy people Healthy people Healthy people Healthy people Mode of injury of case group  Contact 0 62 NA 47 101 0  Non-contact 229 28 NA 51 126 222 NA not available Table 3 Genotype frequencies of VEGFA rs699947 polymorphism in studies included in this meta-analysis References Country Ethnicity HWE Number of samples Genotypes of cases Alleles of cases Minor allele frequency Genotypes of controls Controls’ alleles Minor allele frequency χ 2 P Cases Controls Total A/A A/C C/C A C A/A A/C C/C A C Cięszczyk et al. [ 27 ] South Africa Caucasian 1.5498 0.2131 143 229 372 33 84 26 150 136 0.4755 55 114 60 224 234 0.4890 Shukla et al. [ 28 ] India Indo-Pakistani 0.0112 0.9156 90 76 166 19 51 20 89 91 0.4944 13 30 33 56 96 0.3684 Rahim et al.[ 29 ] South Africa Caucasian 0.5679 0.4510 166 229 395 39 92 35 170 162 0.4879 62 98 69 222 236 0.4847 Rahim et al.[ 30 ] South Africa Colored 0.4862 0.4856 96 95 191 12 48 36 72 120 0.3750 10 44 41 64 126 0.3368 Rahim et al.[ 31 ] South Africa Caucasian 0.3763 0.5395 223 226 449 52 106 65 210 236 0.4708 57 125 44 239 213 0.4712 Lulińska-Kuklik et al. [ 19 ] Poland Caucasian 3.6690 0.05543 222 190 412 39 121 62 199 245 0.4481 25 99 66 149 231 0.3921 HWE Hardy–Weinberg equilibrium, χ 2 Chi-square, NA not available Table 4 Genotype frequencies of VEGFA rs1570360 polymorphism in studies included in this meta-analysis References Country Ethnicity HWE Number of samples Genotypes of cases Alleles of cases Minor allele frequency Genotypes of controls Controls’ alleles Minor allele frequency χ 2 P Cases Controls Total A/A A/G G/G A G A/A A/G G/G A G Rahim et al.[ 29 ] South Africa Caucasian 2.3295 0.1269 160 216 376 20 63 77 103 217 0.3218 32 94 90 158 274 0.3657 Rahim et al.[ 30 ] South Africa Colored 43.5068 0.0001 95 97 192 19 19 57 57 133 0.3000 17 23 57 57 137 0.2938 Rahim et al.[ 31 ] South Africa Caucasian 0.6668 0.4141 224 212 436 21 108 95 150 298 0.3348 28 75 109 131 293 0.3089 Lulińska-Kuklik et al. [ 19 ] Poland Caucasian 1.6655 0.1968 312 190 502 19 95 198 133 491 0.2131 11 69 110 91 289 0.2394 HWE Hardy–Weinberg equilibrium, χ 2 Chi-square, NA not available Table 5 Genotype frequencies of VEGFA rs2010963 polymorphism in studies included in this meta-analysis References Country Ethnicity HWE Number of samples Genotypes of cases Alleles of cases Minor allele frequency Genotypes of controls Controls’ alleles Minor allele frequency χ 2 P Cases Controls Total C/C C/G G/G C G C/C C/G G/G C G Rahim et al.[ 29 ] South Africa Caucasian 0.0228 0.8797 167 232 399 17 77 73 111 223 0.3323 26 101 105 153 311 0.3297 Rahim et al.[ 30 ] South Africa Colored 0.3221 0.5703 99 93 192 7 38 54 52 146 0.2626 7 32 54 46 140 0.2473 Rahim et al.[ 31 ] South Africa Caucasian 0.0774 0.7808 227 226 453 24 99 104 147 307 0.3237 29 101 96 159 293 0.3517 Lulińska-Kuklik et al. [ 19 ] Poland Caucasian 0.0106 0.9176 222 190 412 52 107 63 211 233 0.4752 27 97 66 151 229 0.3973 HWE Hardy–Weinberg equilibrium, χ 2 Chi-square, NA not available Flow diagram of literature searching Main characteristics and quality score of studies included F female, M male, NA not available, ACL anterior cruciate ligament, WHO World Health Organization diagnostic criteria, HWE Hardy–Weinberg equilibrium, a mean ± SD, NA not available Profession and mode of injury in the case groups of included studies NA not available Genotype frequencies of VEGFA rs699947 polymorphism in studies included in this meta-analysis HWE Hardy–Weinberg equilibrium, χ 2 Chi-square, NA not available Genotype frequencies of VEGFA rs1570360 polymorphism in studies included in this meta-analysis HWE Hardy–Weinberg equilibrium, χ 2 Chi-square, NA not available Genotype frequencies of VEGFA rs2010963 polymorphism in studies included in this meta-analysis HWE Hardy–Weinberg equilibrium, χ 2 Chi-square, NA not available Six studies examined the link between VEGFA rs69947 gene polymorphisms and the susceptibility to tendon and ligament injuries. However, none of the five genotypes displayed a significant association. Because four of the articles involved European populations, we performed subgroup analyses. There were no significant differences in the allele, additive, over-dominant, or recessive models. However, in the dominant model, heterogeneity decreased from 66.9 to 33% after removing the study by Lulińska-Kuklik et al. [ 19 ]; a fixed-effect model was then used to further analyze this finding (OR 0.92, 95% CI 0.86–0.98, P  = 0.015). These results indicate that the VEGFA rs699947 AA and AC genotypes are associated with a reduced risk of tendon and ligament injury in European populations (Fig.  2 ). Fig. 2 Forest plots of all selected studies on the association between VEGFA polymorphism and the risk of tendon ligament injury in Europeans ( A rs699947 dominant model, B rs1570360 over-dominant model, C rs2010963 allele model, and D rs2010963 additive model), CI confidence interval, RR risk ratio Forest plots of all selected studies on the association between VEGFA polymorphism and the risk of tendon ligament injury in Europeans ( A rs699947 dominant model, B rs1570360 over-dominant model, C rs2010963 allele model, and D rs2010963 additive model), CI confidence interval, RR risk ratio Four papers investigated gene polymorphisms in VEGFA rs1570360, and there were no significant differences in all gene models. In a subgroup analysis of the European population, the over-dominant model showed a directional change in heterogeneity after removing the study by Rahim et al. [ 31 ]. When this study was excluded, both the AA and GG genotypes in VEGFA rs1570360 increased the risk of tendon and ligament injury in the European population (OR 1.29, 95% CI 1.14–1.45, P  < 0.001, Fig.  2 ). Similarly, four studies investigated the associations between VEGFA rs2010963 gene polymorphisms and tendon and ligament injury risk. There were no significant differences in any of the models. In European populations, the allele and additive gene models had reduced heterogeneity (from 56.2 to 0% and 57.4 to 16.7%, respectively) after removing data from each of two studies by Rahim et al. [ 29 ] and [ 31 ], respectively). In the European population, the G allele in VEGFA rs1570360 had a protective effect against tendon and ligament injury (OR 1.15, 95% CI 1.00–1.32, P  = 0.045, Fig.  2 ), and the GG genotype was associated with a lower risk of tendon and ligament injury than the CC genotype (OR 1.40, 95% CI 1.00–1.94, P  = 0.049). These data are shown in detail in Table  6 and 7 . Table 6 Pooled estimates of association of VEGFA rs699947, rs1570360, and rs2010963 polymorphisms and the risk of tendon injury Genetic model Test of association Tests for heterogeneity Egger’s test OR (95% CI) P P h I 2 (%) P E VEGFA rs699947  A versus C 1.08 (0.88–1.33) 0.455 0.029 59.90 0.184  AA+AC versus CC 1.16 (0.74–1.80) 0.514 0.001 78.30 0.423  AA versus CC 1.13 (0.75–1.71) 0.550 0.048 55.30 0.232  AA versus AC+CC 1.03 (0.83–1.28) 0.792 0.706 0 0.189  AA+CC versus AC 0.90 (0.65–1.26) 0.556 0.005 69.90 0.330 VEGFA rs1570360  A versus G 0.95 (0.81–1.11) 0.511 0.431 0 0.943  AA+AG versus GG 0.96 (0.70–1.31) 0.791 0.088 54.1 0.905  AA versus GG 0.88 (0.63–1.25) 0.484 0.857 0 0.212  AA versus AG+GG 0.88 (0.63–1.22) 0.426 0.661 0 0.117  AA+GG versus AG 1.53 (0.90–2.61) 0.115 0.001 84.4 0.520 VEGFA rs2010963  C versus G 1.07 (0.92–1.25) 0.364 0.163 41.5 0.997  CC+CG versus GG 1.07 (0.87–1.32) 0.523 0.502 0 0.555  CC versus GG 1.16 (0.83–1.62) 0.393 0.124 47.9 0.744  CC versus CG+GG 1.15 (0.84–1.57) 0.371 0.140 45.3 0.580  CC+GG versus CG 1.00 (0.81–1.23) 0.978 0.808 0 0.324 rs699947: allele model: A versus C, dominant model: AA + AC versus CC, additive model: AA versus CC, recessive model: AA versus AC + CC, over-dominant model: AA + CC versus AC rs1570360: allele model: A versus G, dominant model: AA + AG versus GG, additive model: AA versus GG, recessive model: AA versus AG + GG, over-dominant model: AA + GG versus AG rs2010963: allele model: C versus G, dominant model: CC + CG versus GG, additive model: CC versus GG, recessive model: CC versus CG + GG, over-dominant model: CC + GG versus CG Table 7 Pooled estimates of the association of VEGFA rs699947, rs1570360, and rs2010963 polymorphisms with tendon injury risk in Europeans Genetic model Test of association Tests for heterogeneity Egger’s test OR (95% CI) P P h I 2 (%) P E VEGFA rs699947  A versus C 0.98 (0.88–1.10) 0.758 0.109 50.50 0.356  AA + AC versus CC 0.92 (0.86–0.98) 0.015 0.225 33.00 0.075  AA versus CC 0.95 (0.81–1.12) 0.534 0.112 50.00 0.059  AA versus AC+CC 0.99 (0.83–1.17) 0.877 0.377 3.1 0.022  AA+CC versus AC 1.01 (0.83–1.24) 0.910 0.010 73.7 0.787 VEGFA rs1570360  A versus G 0.95 (0.84–1.09) 0.467 0.186 40.5 0.133  AA+AG versus GG 1.01 (0.82–1.24) 0.953 0.085 59.5 0.555  AA versus GG 0.86 (0.61–1.21) 0.381 0.844 0 0.875  AA versus AG+GG 0.84 (0.59–1.19) 0.326 0.678 0 0.006  AA+GG versus AG 1.29(1.14–1.45) 0.001 0.388 0 Na VEGFA rs2010963  C versus G 1.15 (1.00–1.32) 0.045 0.388 0 Na  CC+CG versus GG 1.03 (0.93–1.13) 0.583 0.351 4.4 0.877  CC versus GG 1.40 (1.00–1.94) 0.049 0.273 16.7 Na  CC versus CG+GG 1.12 (0.69–1.82) 0.642 0.094 57.6 0.568  CC+GG versus CG 1.01 (0.91–1.13) 0.799 0.702 0 0.544 rs699947: allele model: A versus C, dominant model: AA+AC versus CC, additive model: AA versus CC, recessive model: AA versus AC+CC, over-dominant model: AA+CC versus AC rs1570360: allele model: A versus G, dominant model: AA+AG versus GG, additive model: AA versus GG, recessive model: AA versus AG+GG, over-dominant model: AA+GG versus AG rs2010963: allele model: C versus G, dominant model: CC+CG versus GG, additive model: CC versus GG, recessive model: CC versus CG+GG, over-dominant model: CC+GG versus CG Statistical significance values are shown in bold, NA: not available Pooled estimates of association of VEGFA rs699947, rs1570360, and rs2010963 polymorphisms and the risk of tendon injury rs699947: allele model: A versus C, dominant model: AA + AC versus CC, additive model: AA versus CC, recessive model: AA versus AC + CC, over-dominant model: AA + CC versus AC rs1570360: allele model: A versus G, dominant model: AA + AG versus GG, additive model: AA versus GG, recessive model: AA versus AG + GG, over-dominant model: AA + GG versus AG rs2010963: allele model: C versus G, dominant model: CC + CG versus GG, additive model: CC versus GG, recessive model: CC versus CG + GG, over-dominant model: CC + GG versus CG Pooled estimates of the association of VEGFA rs699947, rs1570360, and rs2010963 polymorphisms with tendon injury risk in Europeans rs699947: allele model: A versus C, dominant model: AA+AC versus CC, additive model: AA versus CC, recessive model: AA versus AC+CC, over-dominant model: AA+CC versus AC rs1570360: allele model: A versus G, dominant model: AA+AG versus GG, additive model: AA versus GG, recessive model: AA versus AG+GG, over-dominant model: AA+GG versus AG rs2010963: allele model: C versus G, dominant model: CC+CG versus GG, additive model: CC versus GG, recessive model: CC versus CG+GG, over-dominant model: CC+GG versus CG Statistical significance values are shown in bold, NA: not available The meta-analysis found significant heterogeneity between individual studies, possibly due to factors such as race, sex, and age. No subgroup analyses were performed as gender and age were not grouped in the included studies. In the subgroup analysis of races, we found that after the European population excluded Kulik et al. (2019) in the dominant model of rs699947, Rahim et al. [ 31 ] in the over-dominant model of rs1570360, and deleted Rahim et al. [ 29 ] and Rahim et al. [ 31 ] in the allele model and additive model of rs2010963, respectively, the I 2 value changed from > 50 to < 50%, so there were considered as a source of heterogeneity and removed. The studies that remained showed no change in heterogeneity when the included papers were excluded individually. To assess publication bias, both the Egger test and funnel plot were used. The results were relatively stable and there was no clear publication bias, as shown in the funnel chart (Figs. 3 and 4 ) and Egger detailed data (Table  6 and 7 ). Fig. 3 Sensitivity analysis and publication bias funnel plot of the VEGFA polymorphisms and risk of tendon ligament injury Fig. 4 Sensitivity analysis and publication bias funnel plot of the VEGFA polymorphisms and risk of tendon ligament injury in Europeans Sensitivity analysis and publication bias funnel plot of the VEGFA polymorphisms and risk of tendon ligament injury Sensitivity analysis and publication bias funnel plot of the VEGFA polymorphisms and risk of tendon ligament injury in Europeans All positive results are evaluated for FPRP values under various prior probability conditions by OR and 95% CI in order to determine whether they are truly associated with the risk of tendon ligament injury. A FPRP value < 0.2 is considered to indicate high confidence in the results. The confidence tests conducted in this meta-analysis found that the statistically significant positive results were reliable (Table  8 ). Table 8 FPRP values for meta-analysis results Positive result Subgroup Genetic model OR (95% CI) I 2 (%) P Power Prior probability 0.25 0.1 0.01 0.001 0.0001 VEGFA rs699947 Europe AA+AC versus CC 0.92 (0.86–0.98) 33 0.015 1.00 0.028 0.080 0.490 0.906 0.990 VEGFA rs1570360 Europe AA+GG versus AG 1.29 (1.14–1.45) 0  < 0.001 0.994  < 0.001  < 0.001 0.002 0.019 0.165 VEGFA rs2010963 Europe C versus G 1.15 (1.00–1.32) 0 0.045 1.00 0.123 0.297 0.823 0.979 0.998 VEGFA rs2010963 Europe CC versus GG 1.40 (1.00–1.94) 16.7 0.049 0.661 0.164 0.371 0.866 0.985 0.998 Statistical significance values are shown in bold FPRP values for meta-analysis results Statistical significance values are shown in bold VEGF has several commonly studied SNPs (−2578 C/A, −460T/C, −1154 G/A, +405 G/C, and +936 C/T) that may be associated with susceptibility to certain diseases. For instance, Xia Han et al. conducted haplotype analysis and discovered that T–C–T, C–C–C, and C–G–C haplotypes were all genetic susceptibility factors for coronary heart disease (OR: 2.43, 2.77, and 2.33) based on VEGF SNP (−460T/C, −634G/C, and 936C/T) [ 32 ]. Similarly, Eun-Ju Ko et al. found that VEGF −1154G>A, −1498T>C, +936C>T, +1451C>T, +1612G>A, +1725G>A haplotypes G–T–T–C–G, G–C–C–A–A, and A–T–C–G–G were strongly correlated with coronary artery disease sensitivity in their populations [ 33 ]. Haplotype analysis between VEGF −2578 C/A, −460T/C, −1154 G/A, and +405 G/C SNP found that haplotype C–T–G–G had a higher risk of endometriosis than haplotype C–C–G–G and A–T–G–G [ 34 ]. The above studies suggest that the SNPs of VEGF and the haploids that are composed between them do affect the susceptibility of some parts of this population to certain diseases. In this included study, Rahim et al. [ 29 ] found that haploid A–G–G of VEGFA (−2578C/A, −1154G/A, −634C/G) was positively correlated with Achilles tendinopathy. Lulińska-Kuklik et al. [ 19 ] believed that haploid C–G–C of VEGFA (−2578C/A, −1154G/A, −634C/G) increases the risk of ACL injury, while haploid C–G–G has the effect of protecting the ACL.

The current meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. We have registered it prospectively at PROSPERO(CRD42023460376). Relevant literature in the databases, including EMBASE, PubMed Central, Web of Science, Cochrane Library, CNKI, and Wanfang Data Knowledge Service Platform, were searched to analyze the relationship between VEGFA gene polymorphisms and tendon ligament injury. The search strategy was ("vascular endothelial growth factor" or " VEGFA " or "vascular permeability factor" or "VPF") and ("polymorphism" or "variant" or "variation" or "mutation" or "SNP" or "genome-wide association study" or "genetic association study" or "genotype" or "allele") and ("tendon" or "ligament" or "Achilles tendon" or "Anterior cruciate ligament" or "Patellar tendon" or "Elbow tendons"). The search deadline was January 2023. Inclusion Criteria: (1) case–control and cohort studies; (2) correlation between VEGFA rs699947, rs1570360, and rs2010963 polymorphisms and tendon and ligament injuries; (3) detailed control and case group genotype data or their OR with 95% CI. Exclusion criteria: (1) reviews, systematic reviews, case reports, letters, and republished studies; (2) non-case–control studies; (3) literature with incomplete genotypes and irrelevant literature. Two independent researchers extracted data separately using a strict standard protocol. When disagreements arose, they were resolved through discussion or jointly evaluated with a more senior researcher until a consensus was reached. The extracted information includes the first author, publication year, study country, ethnicity, case and control source, participant sex, number of cases and controls, number of distributed genotypes, diagnostic criteria for tendon ligament injury, and investigators' conclusions. The subject selection, inter-group comparability, and outcome measures for all included studies were evaluated using the Newcastle–Ottawa–Scale (NOS). The higher the total score, the higher the quality of the study. The NOS score was divided into three grades: low, medium, and high quality, namely, < 5, 5–7, and 8–9 points. Meta-analysis of data extracted from the included studies was conducted using Stata 17.0 software. The strength of association was assessed using ORs with respective 95% CIs and was considered statistically significant when the P  < 0.05. The study compared five genetic models: allele model, additive model, dominant model, recessive model, and over-dominant model. Additionally, a subgroup analysis was conducted for further investigation. Heterogeneity was evaluated using chi-square-based Q and I 2 values. P  > 0.10 or I 2  < 50% indicated no noteworthy heterogeneity among the included studies, which necessitated the use of a fixed-effect model. When significant heterogeneity was present, a random-effects model was employed. Two sensitivity analyses were performed by (1) removing one of the included studies and (2) eliminating studies that did not comply with Hardy–Weinberg equilibrium (HWE). Egger testing and funnel plots were utilized to identify publication bias, while false-positive report probability (FPRP) was employed to assess confidence in all positive outcomes.

This analysis did not find any significant relationship between VEGFA gene polymorphisms (rs699947, rs1570360, and rs2010963) and the overall risk of tendon and ligament injuries. However, in the European population, individuals with the CC genotype of VEGFA rs699947 have a higher risk of experiencing tendon and ligament injuries. Conversely, those with the AG genotype of rs1570360 demonstrate a protective function against these injuries. At the same time, rs2010963 is significant in evaluating the risk of tendon ligament injury. It was statistically determined that individuals carrying the C allele and those with the CC genotype are highly susceptible to this risk. All of the results were validated by FPRP.

Tendon and ligament injuries commonly arise during physical activity. Incomplete statistics suggest that the likelihood of Achilles tendon injuries in athletes is approximately five times higher than that in the general population [ 10 ]. When tendon ligaments are damaged, it often leads to pain and discomfort, which can significantly impact one's quality of life. Anterior cruciate ligament injuries are mainly non-contact injuries in sports, with offensive running being the most prevalent cause [ 35 ]. Some studies have found that a greater ankle flexion angle does not protect the ACL because the heel does not make full contact with the ground, causing the calf muscles to be unable to fully absorb the reaction force from the ground, increasing stress on the knee joint [ 36 ]. Achilles tendinopathy is caused by the reduction of negative pressure tolerance and continuous overload of the Achilles tendon, which leads to degeneration and failure of healing of the Achilles tendon. Its characteristics mainly include local or diffuse increase in thickness, loss of normal collagen, and loss of normal tissue [ 37 ]. Although the two are not identical in terms of pathology, there may be certain similarities in the underlying causes. Therefore, it is important to identify the cause of tendon ligament injury and prevent its occurrence. There are many causes of tendon ligament injury, and in addition to external factors such as body weight and exercise, genetic contributions are also receiving more and more attention [ 38 ]. Studies have found that VEGF rises to preoperative levels up to 16 times after ACL injury [ 39 , 40 ]. As one of the most potent subtypes, VEGFA could potentially assist in the clinical prevention of tendon ligament injuries by investigating the link between its gene polymorphism and the likelihood of tendon ligament injury. Through statistical analysis, it was found that there was no significant statistical difference between VEGFA rs699947, rs1570360, and rs2010963 gene polymorphisms and the risk of tendon ligament injury without distinguishing populations, and the probability of damage in each genotype was basically the same. In the subgroup analysis of the European population, we found that the population with AA and AC genotypes in the dominant model of VEGFA rs699947 had a lower probability of tendon ligament injury than the population with CC genotype, and the difference was statistically significant. Similarly, in the VEGFA rs1570360 over-dominant model, the AG genotype had a statistically significant difference in protecting tendon ligament injury in the European population compared with other genotypes. Studies have found that the rs1570630 GG genotype is linked to elevated expression of VEGFA. However, the overexpression of VEGFA may also decrease the biomechanical strength of tendons [ 20 ]. Additionally, individuals with the rs1570630 GG genotype tend to be heavier than those with other genotypes [ 41 ], which further raises their risk of tendon and ligament injuries. In the allele model of VEGFA rs2010963, G gene has the effect of reducing tendon ligament injury, and people with GG genotype in the additive model also have a lower risk of tendon ligament injury. This meta-analysis has the following advantages: (1) the relationship between VEGFA rs699947, rs1570360, and rs2010963 gene polymorphisms and the risk of tendon ligament injury was studied for the first time, which was the most innovative in this study; (2) all included studies were assessed and scored in detail; (3) HWE calculations are performed on genotype frequencies to ensure that the final results are true and reliable. However, there are still the following shortcomings in this study: (1) the number of included articles is limited, and the final results may be slightly different from the real results, and this meta is secondary literature and cannot be corrected for multiple tests and report the adjusted p value; (2) there may be some confounding when analyzing across populations because gene frequencies vary between different populations, heterogeneity in some comparisons was not well resolved despite subgroup analyses. Heterogeneity should be considered when interpreting study results, and future studies should focus on more homogeneous patient populations; (3) inability to control factors such as age, gender, weight, and other potential confounding factors may have an impact on the final result; (4) since this subgroup analysis only involved European populations, the results were only for European populations; (5) Although there may be similarities in the genetic susceptibility to Achilles tendinopathy and ACL rupture, the pathologies are not completely identical.

As sports medicine continues to evolve, tendon and ligament injuries are receiving more and more attention. There are approximately 16.5 million reported cases of tendon and ligament injuries in the USA each year, which not only reduces the quality of life of patients, but also increases the socioeconomic burden [ 1 ]. Tendons and ligaments aid in the transmission of muscle strength while upholding joint stability, necessitating them to endure tremendous strain in daily life responsibilities, particularly during physical activity [ 2 ]. According to statistics, a professional soccer player sustains two injuries per season, with a higher likelihood of lower limb injuries. Injuries, such as Achilles tendon and anterior cruciate ligament injuries, can critically impact their athletic careers and daily lives [ 3 , 4 ]. ACL injuries reportedly account for 30% of all knee injuries in high school athletes, with a higher incidence in females than males [ 5 ]. Although materials, such as autologous tendons or artificial tendons, can be used to reconstruct the stability of ligaments, a significant number of patients find it difficult to fully recover to their preoperative physical condition. Additionally, ligament reconstruction is a significant risk factor for postoperative ligament re-rupture [ 6 ]. And more than half of ACL injuries are non-contact injuries [ 7 ]. Achilles tendon disorder is a frequent injury among athletes. The majority of patients occur around the age of 50, according to the study [ 8 ]. Meanwhile, the Danish study revealed that the peak sports injury is in September due to concentrated large-scale activities during the summer, implying that aging and overexertion remain critical factors in exacerbating tendon ligament injury risks [ 8 ]. While exercise does increase the load on the Achilles tendon, studies suggest that 65% of Achilles tendinopathy cases are not related to exercise [ 9 , 10 ]. However, it is important to note that body mass index (BMI) is not a consistent risk factor for tendon and ligament injury. Research has shown that individuals with a high BMI have a lower likelihood of recurrent ACL injury, while those with a low BMI are at a heightened risk of secondary tendon and ligament injury [ 11 ]. The study discovered that women face a higher susceptibility to ACL injury compared to men. This is attributed to women having a greater degree of knee valgus range of motion upon landing [ 12 ]. Similarly, Fares et al. found that the excessively large posterior tibial slope (PTS) is an important risk factor for increased ACL injury [ 13 ]. Tendon ligament injuries are influenced by age, sex, movement style, and location of training. Therefore, preventing these injuries is the key to treatment [ 14 ]. Research has shown that the formation of new blood vessels can greatly affect tendons and ligaments, particularly during injury repair. As a result, promoting the formation of blood vessels via biological and mechanical stimulation can hasten recovery [ 15 ]. VEGFA is a prominent angiogenic agent situated on chromosome 6's short arm. It is made up of an 8-exon and 7-intron coding area of 14-kb and is exceedingly polymorphic [ 16 ]. The most prevalent type of genetic variation is the single-nucleotide polymorphisms (SNPs) that arise from the substitution of just a single nucleotide. SNPs or mutations may relate to the predisposition to diseases, the development of diseases, and the effectiveness of targeted medications [ 17 , 18 ]. The VEGFA promoter contains several typical single-nucleotide polymorphisms (SNPs) that functionally regulate VEGFA expression. These SNPs include −2578C/A (rs699947), −1154G/A (rs1570360), −634C/G (rs2010963), and +936C/T (rs3025039). Among them, rs699947 (C/A), rs1570360 (G/A), and rs2010963 (G/C) are the most commonly studied SNPs associated with angiogenesis, located at the −2578, −1154, and −634 translation start sites in the promoter region [ 16 , 19 ]. VEGFA , the most angiogenic subtype of the five VEGF subtypes, plays a critical role in regulating the extracellular matrix of tendons and ligaments [ 20 ]. Therefore, several studies indicate that genetic variations in VEGFA may be connected to the likelihood of sustaining tendon or ligament injuries [ 21 ]. Research has found that the SP1 TT polymorphism present in the COLIA1 genotype is linked to an increased risk of cruciate ligament injury [ 22 ]. Additionally, the polymorphism of the COL5A1 gene is associated with the risk of Achilles tendon and quadriceps tendon injuries, as well as anterior cruciate ligament tears [ 23 , 24 ]. Furthermore, COL5A1 can interact with the MMP3 gene, which encodes matrix metalloproteinase, thereby heightening the probability of Achilles tendinopathy occurrence [ 25 , 26 ]. This study compares the relationship between rs699947, rs1570360, and rs2010963 gene polymorphisms and tendon ligament injury risk in VEGFA for the first time through meta-analysis, hoping to provide some help for the prevention of related diseases and further personalized treatment.