COL5A1 rs13946 Polymorphism and Anterior Cruciate Ligament Injury: Systematic Review and Meta-Analysis
Year: 2025
Type: review
Study designs: Systematic Review, Meta-Analysis
Abstract: Anterior cruciate ligament (ACL) injury (ACLI) is a prevalent sports injury. Genetic factors play a crucial role in determining the risk of ACLI. This systematic review aimed to identify the association between the COL5A1 rs13946 polymorphism and susceptibility to ACLI. Methods: Searches were performed in PubMed Central, Web of Science, EBSCOhost, Scopus, and CNKI. The Newcastle–Ottawa Scale (NOS) was used to assess potential bias, and data from the included studies were analyzed using RevMan 5.4. The odds ratio (OR) and 95% confidence intervals (95% CI) were calculated to determine the strength of the association between COL5A1 rs13946 and the risk of anterior cruciate ligament injury. A p value < 0.05 was considered statistically significant. Seven studies met the inclusion criteria for screening the association between COL5A1 rs13946 and ACL injury and were included in this meta-analysis. The meta-analysis revealed no significant heterogeneity across five genetic models. Statistically significant findings were observed in the recessive (OR = 1.29, 95% CI [1.06, 1.58], p = 0.01) and allele models (OR = 0.85, 95% CI [0.73, 1.00], p = 0.04). The TT genotype or T allele of rs13946 showed a distinct susceptibility to ACLI under the recessive model, particularly in Caucasians. This study supports the association between COL5A1 rs13946 and the risk of ACLI, particularly in Caucasians. More specifically, the C/- genotype of rs13946 provides protection against ACLI in Caucasians. Further research with larger sample sizes and well-balanced gender-specific cohorts is necessary to validate this association and strengthen our findings.
DOI: 10.3390/ijms26136340
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,499
Funder: Chengdu Normal University
Award: G1715535570
OpenAlex ID: W4411891727
