RESUMEN
Observational studies and clinical trials have reported potential associations between retinal diseases and psychiatric disorders. However, the causal associations between them have remained elusive. In this study, we used bi-directional two-sample Mendelian randomization (MR) analysis to explore unconfounded causal relationships between retinal diseases and psychiatric disorders using large-scale genome-wide association study (GWAS) summary statistics of over 500,000 participants of European ancestry from the FinnGen project, the Psychiatric Genomics Consortium, the European Bioinformatics Institute, and the UK Biobank. Our MR analysis revealed significant causal relationships between major retinal diseases and specific psychiatric disorders. Specifically, susceptibility to dry age-related macular degeneration was associated with a reduced risk of anorexia nervosa (OR = 0.970; 95% CI = 0.930 ~ 0.994; P = 0.025). Furthermore, we found some evidence that exposure to diabetic retinopathy was associated with an increased risk of schizophrenia (OR = 1.021; 95% CI 1.012 ~ 1.049; P = 0.001), and exposure to retinal detachments and breaks was associated with an increased risk of attention deficit hyperactivity disorder (OR = 1.190; 95% CI 1.063 ~ 1.333; P = 0.003). These causal relationships were not confounded by biases of pleiotropy and reverse causation. Our study highlights the importance of preventing and managing retinal disease as a potential avenue for improving the prevention, management and treatment of major psychiatric disorders.
RESUMEN
Background: Alzheimer's disease (AD) is an increasing public health concern with the aging of the global population. Understanding the genetic correlation and potential causal relationships between blood metabolites and AD may provide important insights into the metabolic dysregulation underlying this neurodegenerative disorder. Objective: The aim of this study was to investigate the causal relationship between blood metabolites and AD using Mendelian randomization (MR) analysis. Methods: Association data were obtained from three large-scale genome-wide association studies of 486 blood metabolites (Nâ=â7,824), AD (71,880 cases and 383,378 controls), early-onset AD (Nâ=â303,760), and late-onset AD (Nâ=â307,112). Causal associations between blood metabolites and AD were assessed using inverse variance weighting (IVW), MR-Egger, and weighted median methods. Bidirectional two-sample MR analysis was used to identify causal blood metabolites. MR-PRESSO, MR-Egger, and Cochran-Q were used to quantify instrumental variable heterogeneity and horizontal pleiotropy. Results: Using MR and sensitivity analysis, we identified 40 blood metabolites with potential causal associations with AD. After applying false discovery rate (FDR) correction, two metabolites, gamma-glutamylphenylalanine (ORâ=â1.15, 95% CI: 1.06-1.24, pâ=â3.88×10-4, qâ=â0.09) and X-11317 (ORâ=â1.16, 95% CI: 1.08-1.26, pâ=â1.14×10-4, qâ=â0.05), retained significant associations with AD. Reverse MR analysis indicated no significant causal effect of AD on blood metabolites. No significant instrumental variable heterogeneity or horizontal pleiotropy was found. Conclusions: This two-sample MR study provides compelling evidence for a potential causal relationship between blood metabolic dysregulation and susceptibility to AD. Further investigation of the biological relevance of the identified metabolites to AD and additional supporting evidence is warranted.