Objectives

Disturbances in sleep and waking patterns are highly prevalent during mood episodes in bipolar disorder. The question remains whether these disturbances persist during phases of euthymia and whether they are heritable traits of bipolar disorder. The current study investigates objective sleep measures in a large sample of bipolar I patients, non-affected siblings and controls.

Methods

A total of 107 bipolar disorder I patients, 74 non-affected siblings, and 80 controls were included. Sleep was measured with actigraphy over the course of 14 days. Seven sleep parameters were analyzed for group differences and their relationship with age at onset, number of episodes and psychotic symptoms using linear mixed model analysis to account for family dependencies.

Results

Patients had a longer sleep duration and later time of sleep offset compared to the non-affected siblings but these differences were entirely attributable to differences in mood symptoms. We found no difference between patients and controls or siblings and controls when the analyses were restricted to euthymic patients. None of the bipolar illness characteristics were associated with sleep.

Limitations

Medication use was not taken into account which may have influenced our findings and controls were younger compared to non-affected siblings.

Conclusions

In the largest study to date, our findings suggest that recovered bipolar I patients and their siblings do not experience clinically significant sleep disturbances. Sleep disturbances are primarily a reflection of current mood state, but are unrelated to the course of the disorder.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.