Mendelian randomization shows depression increase the risk of type 2 diabetes

Abstract

Abstract Type 2 diabetes (T2D) is associated with severe mental illnesses (SMIs), such as schizophrenia, bipolar disorder, and depression. However, causal relationships between SMIs and T2D remain unclear owing to potential bias in observational studies. We aimed to characterize the causal effect of SMI liability on T2D using two-sample Mendelian randomization (MR). The causality between liability to SMI and T2D was investigated using the inverse-variance weighted (IVW), MR-Egger, MR-Egger with a simulation extrapolation, weighted median, and the MR pleiotropy residual sum and outlier method. Similarly, we performed additional MR which can detect the reverse causation effect by switching exposure and outcome for T2D liability for SMI. To further consider pleiotropic effects between SMIs, multivariable MR analysis was performed after accounting for the other traits. In the univariable IVW method, depression showed a causal effect on T2D (odds ratio [OR]: 1.128, 95% confidence interval [CI]: 1.024–1.245, P = 0.014). Multinomial MR more strongly supported these results (IVW OR: 1.197, 95% CI: 1.069, 1.340, P = 0.002; MR-Egger OR: 1.198, 95% CI: 1.062, 1.349, P = 0.003). Bidirectional MR showed reverse-causality absence between depression and T2D. However, causal relationship of bipolar and schizophrenia on T2D was not detected. Careful attention is needed for patients with depression regarding T2D prevention and treatment.