Investigating the causal relationship between diabetes and shoulder periarthritis: A 2-sample Mendelian randomization...

This study aimed to explore the potential causal relationship between diabetes and shoulder periarthritis using the Mendelian randomization (MR) approach. Pooled data from large-scale genome-wide association studies were used to identify single nucleotide polymorphisms associated with type 2 diabetes (T2D), rather than a combined diabetes phenotype. T2D was selected as the exposure because existing clinical and epidemiological evidence links shoulder periarthritis primarily to metabolic dysfunction and insulin resistance characteristic of T2D, ensuring genetic independence between the 2. These single nucleotide polymorphisms were used as instrumental variables in a 2-sample MR analysis. The study primarily focused on European populations from publicly available databases. Multiple MR methods (inverse variance weighting, weighted median estimator, and MR-Egger regression) were employed to enhance result robustness. Heterogeneity tests, pleiotropy assessments, and "leave-one-out" sensitivity analyses were performed to validate the findings. The inverse variance weighting analysis showed that the causal effect of diabetes on shoulder periarthritis was odds ratio = 1.00 (95% confidence interval: 0.96-1.04, P = .822), indicating no significant association between diabetes and an increased risk of shoulder periarthritis. Further multi-effect tests revealed no bias, and sensitivity analyses supported the robustness of these results. This 2-sample MR analysis suggests that, based on current genetic data from European populations, diabetes is not an independent causal factor for shoulder periarthritis. These findings offer a genetic perspective on the epidemiological relationship between the 2 conditions, providing clinicians with insights for more accurate identification of risk factors when developing intervention strategies.