Sleep-Related and Chronobiology Traits and Health-Related Phenotypes: A Phenome-Wide Mendelian Randomisation Study

Sleep-related and chronotype traits have been shown to impact health in observational studies. To identify whether these associations are potentially causal, we conducted phenome-wide Mendelian randomisation analyses of short sleep, insomnia symptoms, total sleep duration, long sleep, snoring, daytime sleepiness and morning chronotype with a broad range of health-related phenotypes. We assessed the association between the genetic predisposition to these traits and the occurrence of 702 health-related phenotypes, using summary statistics of the largest genome-wide association studies in European individuals. Results that were significant (multiple comparisons: False Discovery Rate) and valid (robust genetic instruments, unaffected by horizontal pleiotropy) were validated using data from the second largest European genome-wide association study. Genetically determined short sleep was associated with increased risks of attention-deficit/hyperactivity disorder and neuroticism, musculoskeletal conditions, asthma and gastroesophageal reflux and lower educational attainment. Genetically determined insomnia symptoms showed associations with increased risk of coronary artery disease, major depression and osteoarticular disease. Genetically determined long sleep was linked to higher risk of iron deficiency anaemia and lower bone mineral density. Genetic predisposition to snoring was associated with more falls, greater body mass and higher low-grade inflammation. Genetically determined morning chronotype was related to higher vitamin D levels and lower risk of irritable bowel syndrome. No associations were found for daytime sleepiness. Overall, these findings indicate that genetically determined short sleep duration and insomnia symptoms are associated with mental and neurological problems, cardiovascular disease and musculoskeletal disorders, suggesting a potentially preventive, causal role of healthy sleeping patterns on chronic disease.