ABSTRACT Background Observational studies suggest an association between social isolation and cannabis use disorder (CUD), but causality remains unclear. This study employs Mendelian randomization (MR) to assess the potential causal effect of social isolation on CUD and explore the mediating role of anxiety disorders and depression. Methods GWAS summary statistics for social isolation, CUD, anxiety disorders, and depression were obtained from public GWAS repositories. Inverse variance weighted (IVW) was the primary MR method, supplemented by MR‐Egger, weighted median, and maximum likelihood approaches to evaluate: (i) The causal effect of social isolation on CUD; (ii) its effect on anxiety disorders and depression; (iii) the effect of anxiety disorders and depression on CUD. Sensitivity analyses included Cochran's Q test for heterogeneity, MR‐Egger intercept and MR‐PRESSO for pleiotropy, and leave‐one‐out analysis for robustness. The mediation effect was quantified using the delta method. Results IVW analysis revealed a significant positive correlation between social isolation and increased CUD risk (OR = 4.29, 95% CI: 1.35–13.64, p = 0.014), with supplementary MR methods yielding consistent results (OR > 1). Sensitivity analyses confirmed the robustness of findings. In addition, the mediation MR analysis revealed that depression significantly mediated the causal effect of social isolation on CUD. Specifically, social isolation showed a significant positive association with depression risk (OR = 3.70, 95% CI: 2.32–5.89, p = 3.67E‐08), and depression, in turn, was positively associated with an increased risk of CUD (OR = 1.27, 95% CI: 1.08–1.50, p = 0.003). The delta method indicated that depression mediated 21.8% of the effect of social isolation on CUD risk. Conclusions Social isolation is potentially associated with an increased risk of CUD, with depression as a key mediator. The findings should be considered in light of limitations including potential recall bias, European ancestry samples, and the inability to assess exposure‐mediator interactions using summary‐level data.
Tao Ma (2025) studied this question.