Abstract
BACKGROUND: The association between depression and musculoskeletal diseases has long been a subject of contentious debate. However, the causal relationship between the two remains uncertain. This study employs a two-sample Mendelian randomization (MR) analysis to investigate the causality between depression and six musculoskeletal diseases. METHODS: In this study, we performed MR analysis to systematically explore the causal relationship between depression and six musculoskeletal disorders. Single nucleotide polymorphisms (SNPs) that are linked to depression were employed as instrumental variables. To ensure robust and reliable conclusions, multiple analytical approaches were utilized, including inverse variance weighting(IVW), weighted median, and MR-Egger regression. Additionally, sensitivity analysis methods such as the MR-Egger intercept test, Cochran's Q test, leave-one-out analysis, and funnel plot were employed. RESULTS: Our MR analysis revealed a significant association between depression and cervical spondylosis (depression: OR 1.003, 95% CI 1.002-1.005, P = 8.32E-05; major depressive disorder: OR 1.003, 95% CI 1.001-1.005, P = 0.0052). Furthermore, a strong correlation was noted between major depressive disorder (MDD) and knee osteoarthritis (KOA) (OR 1.299, 95% CI 1.154-1.463, P = 1.50E-5). Sensitivity analysis confirmed the robustness of these findings. Our independent validation study also corroborated these results. CONCLUSION: The MR analysis conducted in this study provides evidence supporting a genetic link between depression and cervical spondylosis, as well as KOA. Targeted interventions to manage depression in susceptible populations may contribute to lowering the risk of cervical spondylosis and KOA in these cohorts.