Integrative Modeling of Accelerometry-Derived Sleep, Physical Activity, and Circadian Rhythm Domains With Current or Remitted Major Depression

Author:

Kang Sun Jung1,Leroux Andrew2,Guo Wei1,Dey Debangan1,Strippoli Marie-Pierre F.3,Di Junrui4,Vaucher Julien56,Marques-Vidal Pedro6,Vollenweider Peter6,Preisig Martin3,Merikangas Kathleen R.14,Zipunnikov Vadim4

Affiliation:

1. Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland

2. Department of Biostatistics and Informatics, University of Colorado, Anschutz Medical Campus, Aurora

3. Psychiatric Epidemiology and Psychopathology Research Center, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland

4. Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

5. Service of Internal Medicine, Department of Medicine and Specialties, Fribourg Hospital and University of Fribourg, Switzerland

6. Service of Internal Medicine, Department of Medicine, Lausanne University Hospital and University of Lausanne, Switzerland

Abstract

ImportanceAccelerometry has been increasingly used as an objective index of sleep, physical activity, and circadian rhythms in people with mood disorders. However, most prior research has focused on sleep or physical activity alone without consideration of the strong within- and cross-domain intercorrelations; and few studies have distinguished between trait and state profiles of accelerometry domains in major depressive disorder (MDD).ObjectivesTo identify joint and individual components of the domains derived from accelerometry, including sleep, physical activity, and circadian rhythmicity using the Joint and Individual Variation Explained method (JIVE), a novel multimodal integrative dimension-reduction technique; and to examine associations between joint and individual components with current and remitted MDD.Design, Setting, and ParticipantsThis cross-sectional study examined data from the second wave of a population cohort study from Lausanne, Switzerland. Participants included 2317 adults (1164 without MDD, 185 with current MDD, and 968 with remitted MDD) with accelerometry for at least 7 days. Statistical analysis was conducted from January 2021 to June 2023.Main Outcomes and MeasuresFeatures derived from accelerometry for 14 days; current and remitted MDD. Logistic regression adjusted for age, sex, body mass index, and anxiety and substance use disorders.ResultsAmong 2317 adults included in the study, 1261 (54.42%) were female, and mean (SD) age was 61.79 (9.97) years. JIVE reduced 28 accelerometry features to 3 joint and 6 individual components (1 sleep, 2 physical activity, 3 circadian rhythms). Joint components explained 58.5%, 79.5%, 54.5% of the total variation in sleep, physical activity, and circadian rhythm domains, respectively. Both current and remitted depression were associated with the first 2 joint components that were distinguished by the salience of high-intensity physical activity and amplitude of circadian rhythm and timing of both sleep and physical activity, respectively. MDD had significantly weaker circadian rhythmicity.Conclusions and RelevanceApplication of a novel multimodal dimension-reduction technique demonstrates the importance of joint influences of physical activity, circadian rhythms, and timing of both sleep and physical activity with MDD; dampened circadian rhythmicity may constitute a trait marker for MDD. This work illustrates the value of accelerometry as a potential biomarker for subtypes of depression and highlights the importance of consideration of the full 24-hour sleep-wake cycle in future studies.

Publisher

American Medical Association (AMA)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Errors in Results and Supplement 1;JAMA Psychiatry;2024-09-01

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