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Major depression (MD) is a well-recognized risk factor for delirium. However, observational studies cannot provide direct evidence of causality between MD and delirium. This study explored the genetic causal association between MD and delirium using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for MD were obtained from the UK Biobank. GWAS summary data for delirium were obtained from the FinnGen Consortium. Inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were used to perform the MR analysis. In addition, the Cochrane's Q test was used to detect heterogeneity in the MR results. Horizontal pleiotropy was detected using the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. Leave-one-out analysis was used to investigate the sensitivity of this association. The IVW method showed that MD was an independent risk factor for delirium (P = 0.013). Horizontal pleiotropy was unlikely to bias causality (P > 0.05), and no evidence of heterogeneity was found between the genetic variants (P > 0.05). Finally, a leave-one-out test showed that this association was stable and robust. All participants included in the GWAS were of European ancestry. Due to database limitations, the MR analysis did not conduct stratified analyses for different countries, ethnicities, or age groups. We conducted a two-sample MR analysis and found the evidence of genetic causal association between MD and delirium. • A two-sample MR analysis was conducted to explore the causal effect between MD and delirium. • Inverse-variance weighted, MR Egger, weighted median, simple mode, and weighted mode were used to perform the MR analysis. • Heterogeneity and horizontal pleiotropy in the MR results were detected. • We found the evidence of genetic causal association between MD and delirium. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]