Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine - Tập 18 Số 10 - Trang e1003782
Michael Wainberg1, Samuel E. Jones2,3, Lindsay Melhuish Beaupre4,5, Sean Hill6,7,5,1, Daniel Felsky8,7,5,1, Manuel A. Rivas9, Andrew Lim10,11, Hanna M. Ollila12,13,2,14, Shreejoy J. Tripathy6,7,5,1
1Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, Canada
2Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
3University of Exeter Medical School, Exeter, United Kingdom
4Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
5Institute of Medical Sciences, University of Toronto, Toronto, Canada
6Department of Physiology, University of Toronto, Toronto, Canada
7Department of Psychiatry, University of Toronto, Toronto, Canada
8Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
9Department of Genetics, Stanford University, Stanford, California, United States of America
10Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
11Sunnybrook Health Sciences Centre, Toronto, Canada
12Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
13Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
14Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America

Tóm tắt

BackgroundSleep 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 findingsIn 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.ConclusionsIn 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.

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PLoS Medicine

Tập 18 Số 10

e1003782

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