Exploring the Causal Association between Morning Diurnal Preference and Psychiatric Disorders: A Bidirectional Two-Sample Mendelian Randomization Analysis.

Abstract

The causal connection between morning diurnal preference and psychiatric disorders remains enigmatic. Using bidirectional two-sample Mendelian randomization (MR), we aim to explore the potential causal associations between morning diurnal preference and seven prominent psychiatric disorders. MR is a genetic epidemiological method that leverages genetic variants as instrumental variables to infer causal associations between exposures and outcomes. We obtained morning diurnal preference data from genome-wide association study (GWAS) datasets and identified 252,287 individuals as morning people. Psychiatric disorder data were sourced from the FinnGen consortium R9 dataset. Our primary analysis used the inverse-variance weighted (IVW) approach to evaluate the overall causal effect by combining the estimates from each genetic variant. Addition analyses, including weighted median, MR-Egger regression, weighted mode, and simple mode techniques were conducted to ensure robustness. Being a morning person is related to reduced odds of multiple psychiatric disorders, including depression or dysthymia (OR: 0.93, 95% CI: 0.88, 0.999), anxiety disorders (OR: 0.90, 95% CI: 0.84, 0.96), self-harming behaviors (OR: 0.87, 95% CI: 0.76, 0.99), substance-use disorders (OR: 0.81, 95% CI: 0.71, 0.93), alcohol dependence (OR: 0.82, 95% CI: 0.73, 0.92), alcohol use disorders (OR: 0.85, 95% CI: 0.76, 0.94), acute alcohol intoxication (OR: 0.86, 95% CI: 0.76, 0.96), schizophrenia (OR: 0.77, 95% CI: 0.65, 0.92), and schizophrenia or delusion (OR: 0.80, 95% CI: 0.70, 0.92). Alcohol dependence (OR: 0.97, 95% CI: 0.94, 0.999) and alcohol use disorders (OR: 0.96, 95% CI: 0.94, 0.99) were also related to a lower morning diurnal preference. Our study provides evidence that being a morning person is a protective factor for various psychiatric disorders from a genetic perspective. The results provide insights for potential targeted interventions to improve mental wellbeing.