Genetic evidence for behavioral preference factors on fatigue: A Mendelian randomization study of chronotype, morning alertness, and outdoor exposure

Fatigue is a multifactorial condition influenced by environmental, behavioral, genetic, and disease-related factors. While observational studies have identified key contributors like circadian disruption, sleep disturbances, and genetic predisposition, the causal relationships remain unclear. Mendelian randomization (MR) offers a robust approach to overcome limitations of traditional studies and establish causal links between modifiable behavioral preferences and fatigue. This study employed univariate and multivariate MR (MVMR) analyses using publicly available genome-wide association study (GWAS) summary statistics to investigate the potential causal relationships between these behavioral preference factors and the risk of fatigue. We obtained GWAS summary statistics for relevant variables from the Neale Lab and MRC Integrated Epidemiology Unit (MRC-IEU) databases. After systematic screening of multiple domains (internal microenvironment, indoor environment parameters, and natural environment characteristics), the inverse variance weighted (IVW) method served as the primary analysis, complemented by sensitivity analysis (heterogeneity test, pleiotropy analysis, leave-one-out analysis, and MR-PRESSO) to evaluate result robustness. Using GWAS data from 32 traits (1645,048 participants), we identified three significant behavioral preference-related determinants of fatigue: chronotype, ease of getting up in the morning, and time spent outdoors in summer. The MR results demonstrated: Protective effects against fatigue associated with greater ease of getting up in the morning (OR = 0.991, 95%CI 0.987–0.995; P  < .001) and longer summer outdoor exposure (OR = 0.996, 95%CI 0.992–1.000; P  = .030); Elevated fatigue risk,linked to evening chronotype (OR = 1.003, 95%CI 1.001–1.005; P  = .013). MVMR analysis showed that after jointly incorporating variables, the impact of ease of getting up in the morning on fatigue remained significant (OR = 0.987, 95%CI: 0.980–0.995, P  = .002). Sensitivity analyses confirmed the robustness of these findings: although significant heterogeneity was detected for ease of getting up in the morning (Cochran’s Q test P  < .05), no evidence of horizontal pleiotropy (MR-Egger intercept P  > .05) or outlier SNPs (MR-PRESSO) was found, and results were consistent across multiple MR methods. These findings provide genetic evidence supporting causal relationships between modifiable behavioral preference factors and fatigue. Specifically, greater ease of getting up in the morning and longer summer outdoor exposure may reduce fatigue risk, while evening chronotype increases susceptibility.