Abstract
The aim of this study was to assess whether diabetes mellitus is a potential causal factor in the development of meniscal injuries by means of Mendelian randomization (MR). Independent genetic variants strongly associated with diabetes mellitus and representative of European populations were selected as instrumental variables using large-scale genome-wide association studies (GWAS) pooled data to explore causal associations. In this study, SNPs meeting the prerequisites of MR analysis were selected as instrumental variables, and 3 mainstream MR methods, including the inverse variance weighted (IVW) method, the weighted median (WME) method, and the MR-Egger regression analysis, were used for the estimation of the causal effects, respectively. In order to assess the robustness and reliability of the model, further heterogeneity test (Cochran Q test) and multiple validity test (MR-Egger intercept term and MR-PRESSO global test) were conducted, and leave-one-out analysis was applied to systematically assess the sensitivity of the model. The results of IVW analysis showed that the effect of diabetes mellitus on meniscal injuries was not statistically significant (OR = 0.99, 95% CI: 0.95-1.03, P = .733), suggesting a lack of a clear causal link between the 2. In addition, the results of heterogeneity test showed no significant heterogeneity, and the multiplicity analyses of MR-Egger and MR-PRESSO did not find any potential bias, and the "leave-one-out" method further proved that the results had good stability and reliability. This study was a preliminary investigation of the causal relationship between diabetes mellitus and meniscal injuries based on a two-sample MR approach. The results failed to find a direct causal effect of diabetes mellitus on meniscal injuries, suggesting that the relationship may be more influenced by other confounding factors. In the future, more samples and larger-scale genetic data should be included to further validate and improve the findings.