BACKGROUND

Numerous studies have documented the effects of daytime napping, sleep duration, and depression on cardiovascular diseases (CVDs). However, the evidence has been gleaned from observational studies that might be riddled with confounding variables and the possibility of reverse causation bias. Therefore, the present study employed a Mendelian randomization (MR) methodology to meticulously explore the relationships between daytime napping, sleep duration, and depression, and the risk profiles of CVDs.

METHODS

Genome-wide significant genetic variants associated with daytime napping, sleep duration, and depression were used as the instrumental variables (IVs). Data on the genetic correlations between these IVs and 15 CVDs were derived from the United Kingdom (UK) Biobank, Finnish Genome Studies, and other large-scale collaborations. We conducted both univariate and multivariate MR analyses to assess the overall effects and mediated relationships after adjusting for potential confounders, including body mass index (BMI), smoking status, and type 2 diabetes. The effect sizes were estimated using inverse variance-weighted (IVW) regression.

RESULTS

The MR analysis revealed that an increased risk of heart failure (HF) [odds ratio (OR): 1.366; 95% confidence interval (CI): 1.013-1.842; P=0.04], coronary atherosclerosis (OR: 1.918; 95% CI: 1.257-2.927; P=0.003), myocardial infarction (MI) (OR: 1.505; 95% CI: 1.025-2.211; P=0.04), and coronary artery disease (CAD) (OR: 1.519; 95% CI: 1.130-2.043; P=0.006) was significantly associated with genetically predicted daytime napping. Prolonged sleep duration was found to be related to a reduced risk of HF (OR: 0.995; 95% CI: 0.993-0.998; P=2.69E-04), peripheral vascular disease (PVD) (OR: 0.984; 95% CI: 0.971-0.997; P=0.02), and CAD (OR: 0.997; 95% CI: 0.994-0.999; P=0.006). Additionally, a statistically significant positive relationship was observed between depressive disorders and the occurrence of atrial fibrillation (AF) (OR: 1.298, 95% CI: 1.065-1.583, P=0.01), indicating a heightened susceptibility. The multivariable MR analyses substantiated the reliability of the observed associations between daytime napping and the incidence of HF and CAD, following adjustments for genetically predicted BMI and smoking. The sensitivity analysis did not reveal any evidence of horizontal pleiotropy or heterogeneity, thus supporting the validity of the study's results.

CONCLUSIONS

This MR investigation posits a potential causal nexus between daytime napping, sleep duration, and depression, and the genesis of CVDs, offering new perspectives on the prevention and management of CVDs.