Causal association between mental disorders and cerebrovascular diseases: Evidence from Mendelian randomization study.

Background And Objective: Observational studies have suggested that mental disorders and cerebrovascular diseases (CVDs) may be risk factors for each other, but genetic evidence of a causal relationship is still lacking. We used Mendelian randomization (MR) studies to explore the causal relationship between mental disorders and CVDs from the genetic perspective.

Methods: To investigate the causal association between major depressive disorder (MDD), anxiety, attention deficit/hyperactivity disorder (ADHD), bipolar disorder and schizophrenia five kinds of mental disorders and CVDs using two-sample two-way MR analysis based on publicly available genome-wide association study (GWAS) data. We used as instrumental variables (IVs) single-nucleotide polymorphisms (SNPs) that were strongly associated with mental disorders and CVDs. IVW method was used as the main analysis method, and MR-IVW, MR-Egger methods, MR-PRESSO test, leave-one-out analysis and funnel plot were used for sensitivity analysis. We further conducted a meta-analysis to summarize the currently available MR analyses.

Results: The results of forward MR study showed that there was a significant causal relationship between ADHD and AS (any stroke) (p = 0.001, OR (95%CI) =1.118 (1.047-1.195)), any ischemic stroke (AIS) (p = 0.004, OR (95%CI) =1.118(1.035-1.206)) and large artery stroke (LAS) (p = 0.026, OR (95%CI): 1.206(1.023-1.422)). No heterogeneity, pleiotropy and outliers were found in sensitivity analysis. The reverse MR study showed that IA (intracranial aneurysm) (p = 0.033, OR (95%CI) = 1.123(1.009-1.249)) and UIA (unruptured intracranial aneurysm) (p = 0.015, OR (95%CI) =1.040(1.008-1.074)) were risk factors for schizophrenia. Sensitivity analysis showed no pleiotropy, but there was heterogeneity. After excluding outliers, MR analysis showed that IA and UIA were still risk factors for schizophrenia. Our meta-analyses found statistical significance in causal relationships between ADHD and LAS (OR (95%CI) =1.18 (1.06-1.32), p = 0.003), IA and schizophrenia (OR (95%CI) =1.05 (1.02-1.08), p = 0.002) and UIA and schizophrenia (OR (95%CI) =1.03 (1.01-1.06), p = 0.010).

Conclusion: The MR study and meta-analysis suggest that genetically predicted ADHD is a risk factor for LAS, and IA and UIA increase the risk of schizophrenia. The result has implications for the development of feasible prevention strategies in the future.