Genomic Landscape of Phenotypes Causally Associated with Night Shift Work
Xing Jin, Yang Yang, Jie Xu, Hui LiuObjective:
To apply an MR-PheWAS to infer causality between NSW and multiple health outcomes.
Methods:
This study used MR-PheWAS to assess the causal effects of NSW on 18,115 health traits, applying IVW, MR-Egger, Wald ratio, and sensitivity analyses to classify associations by evidence strength.
Results:
MR-PheWAS identified 1,278 phenotypes associated with NSW frequency, 918 with intensity, and 199 with history, including lower risks of hypertrophic skin disorders, endometriosis, and cardiomyopathies, but higher risks of gestational hypertension, androgenic alopecia, pulmonary eosinophilia, multiple sclerosis, primary ovarian failure, structural brain changes, stroke, diabetes, neuroticism, chronic renal failure, chronic hepatitis B, and hypertension.
Conclusion:
This study demonstrates that NSW broadly affects multiple health outcomes, including neuroimaging phenotypes reflecting functional and structural alterations, highlighting the need for public health strategies and further research to clarify mechanisms and develop targeted interventions.