Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.
Melatonin is an ancient molecule that is evident in high concentrations in various tissues throughout the body. It can be separated into two pools; one of which is synthesized by the pineal and can be found in blood, and the second by various tissues and is present in these tissues. Pineal melatonin levels display a circadian rhythm while tissue melatonin does not. For decades now, melatonin has been implicated in promoting and maintaining sleep. More recently, evidence indicates that it also plays an important role in neuroprotection. The beginning of our review will summarize this literature. As an amphiphilic, pleiotropic indoleamine, melatonin has both direct actions and receptor-mediated effects. For example, melatonin has established effects as an antioxidant and free radical scavenger both in vitro and in animal models. This is also evident in melatonin’s prominent role in mitochondria, which is reviewed in the next section. Melatonin is synthesized in, taken up by, and concentrated in mitochondria, the powerhouse of the cell. Mitochondria are also the major source of reactive oxygen species as a byproduct of mitochondrial oxidative metabolism. The final section of our review summarizes melatonin’s potential role in aging and psychiatric disorders. Pineal and tissue melatonin levels both decline with age. Pineal melatonin declines in individuals suffering from psychiatric disorders. Melatonin’s ability to act as a neuroprotectant opens new avenues of exploration for the molecule as it may be a potential treatment for cases with neurodegenerative disease.
Purposes/Background Antidepressants (ADs) play a valuable role in treating the depressive episodes of bipolar disorder. However, 14% of these individuals taking ADs experience AD-associated mania (AAM) within a few weeks of starting treatment. Numerous studies have suggested potential clinical and genetic risk factors. We aimed to conduct a comprehensive systematic review and meta-analysis that integrates the past literature with the recent studies and identifies important predictors for AAM. Methods/Procedures The review was limited to experimentally designed studies that contain the relevant search terms in PubMed and PsychInfo. After removing studies that were in discordance with our criteria, the review included 24 reports examining clinical risk factors and 10 investigating genetic risk factors. Our meta-analysis was conducted on 5 clinical risk factors, each of which had at least 4 articles with extractable data. Findings/Results The only clinical factors in the literature that have been shown to be more indicative of AAM risk are AD monotherapy and tricyclic ADs. Among genetic factors, the serotonin transporter gene polymorphism may play a minor role in AAM. Our meta-analysis provided support for the number of prior depressive episodes. Implications/Conclusion Prevention of AAM may be served by early detection of recurrent depression episodes. Further large-scale longitudinal studies are required to determine the underpinnings of AAM.
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