Background: Rheumatoid arthritis (RA) increases the risk of depression. However, studies on the effects of RA on the dose of depression medications are limited. Therefore, in this study, we used two-sample Mendelian randomization (MR) to explore whether RA increases the dose of depression medications and gain a more comprehensive understanding of the relationship between RA and depression. Methods: Two-sample MR was used to evaluate the causal effect of RA on the dose of depression medications. The aggregated data on RA originated from extensive genome-wide association studies (GWASs) of European descent (14,361 cases and 42,923 controls). The summary GWAS data for the dose of depression medications were derived from the FinnGen consortium (58,842 cases and 59,827 controls). Random effects inverse-variance weighted (IVW), MR-Egger regression, weighted median, and fixed effects IVW methods were used for the MR analysis. Random effects IVW was the primary method. The heterogeneity of the MR results was detected using the IVW Cochran’s Q test. The pleiotropy of the MR results was detected using MR-Egger regression and the MR pleiotropy residual sum and outlier (MR-PRESSO) test. Finally, a leave-one-out analysis was performed to determine whether the MR results were affected by a specific single-nucleotide polymorphism (SNP). Results: The primary method, random effects IVW, revealed that genetically predicted RA had a positive causal association with the dose of depression medications (Beta, 0.035; 95% confidence interval (CI), 0.007–0.064; p = 0.015). The IVW Cochran’s Q test results revealed no heterogeneity in the MR analysis (p > 0.05). The MR-Egger regression and MR-PRESSO tests revealed that there was no pleiotropy in our MR analysis. The leave-one-out analysis confirmed that a single SNP did not affect the MR results, indicating the study’s robustness. Conclusion: Using MR techniques, we discovered that having RA increases the dose of depression medications; however, the exact mechanisms and pathways still need to be further explored.

Based on previous observational studies, the causal association between circulating adiponectin (CA) levels and ankylosing spondylitis (AS) risk remains unclear. Therefore, this study aims to investigate whether CA levels are related to the risk of AS. We carried out a bidirectional two-sample Mendelian randomization (MR) analysis to examine the causal correlation between CA levels and AS via published genome-wide association study (GWAS) datasets. Single-nucleotide polymorphisms (SNPs) related to CA levels were derived from a large GWAS that included 39,883 individuals of European descent. SNPs related to AS were obtained from the FinnGen consortium (2252 cases and 227,338 controls). The random-effects inverse variance weighted (IVW) method was the primary method utilized in our research. We also used four complementary approaches to improve the dependability of this study (MR–Egger regression, Weighted median, Weighted mode, and Simple mode). Random-effects IVW (odds ratio [OR], 1.00; 95% confidence interval [CI], 0.79–1.27, p = 0.984) and four complementary methods all indicated that genetically predicted CA levels were not causally related to the risk of AS. In reverse MR analysis, there is little evidence to support the genetic causality between the risk of AS and CA levels.