Daytime midpoint as a digital biomarker for chronotype in bipolar disorder

• Main Authors: Depp, C.A (Author), Gershon, A. (Author), Kaufmann, C.N (Author), Ketter, T.A (Author), Miller, S. (Author), Zeitzer, J.M (Author)
• Format: Article
• Language: English
• Published: Elsevier B.V. 2018
• Subjects: Actigraphy; actimetry; adolescent; Adolescent; adult; Adult; Article; biological marker; Biomarkers; bipolar disorder; Bipolar disorder; Bipolar Disorder; bipolar I disorder; bipolar II disorder; Chronobiology Disorders; chronotropism; Chronotype; circadian rhythm; Circadian Rhythm; Composite Scale of Morningness; controlled study; Daytime; female; Female; human; Humans; major clinical study; male; Male; middle aged; Middle Aged; priority journal; psychology; questionnaire; rating scale; sleep; Sleep; sleep disorder; Surveys and Questionnaires; young adult; Young Adult
• Online Access: View Fulltext in Publisher

 Background: Bipolar disorder (BD) is associated with later sleep and daily activity (evening rather than morning chronotype). Objective chronotype identification (e.g., based on actigraphs/smartphones) has potential utility, but to date, chronotype has mostly been assessed by questionnaires. Given the ubiquity of accelerometer-based devices (e.g. actigraphs/smartphones) worn/used during daytime and tendency to recharge rather than wear at night, we assessed chronotype using daytime (rather than sleep) interval midpoints. Methods: Sixty-one participants with BD type I (BD-I) or II (BD-II) and 61 healthy controls completed 25–50 days of continuous actigraphy. The Composite Scale of Morningness (CSM) was completed by a subset of this group. Daytime activity midpoint was calculated for each daytime interval, excluding naps. Evening chronotype was defined as having a daytime interval midpoint at or after 16:15:00 (4:15:00 PM). Results: BD versus controls had delayed daytime midpoint (mean ± standard deviation) (16:49:07 ± 01:26:19 versus 16:12:51 ± 01:02:14, p < 0.01), and greater midpoint variability (73.3 ± 33.9 min versus 58.1 ± 18.3 min, p < 0.01). Stratifying by gender and age, females and adolescents with BD had delayed and more variable daytime midpoints versus controls. Adults with BD had greater midpoint variability than controls. Within-person mean and standard deviations of daytime midpoints were highly correlated with sleep midpoints (r = 0.99, p < 0.01 and r = 0.86, p < 0.01, respectively). Daytime midpoint mean was also significantly correlated with the CSM (r = -0.56, p < 0.01). Limitations: Small sample size; analyses not fully accounting for daytime napping. Conclusions: Wrist actigraphy for determination of daytime midpoints is a potential tool to identify objective chronotype. Exploration of the use of consumer devices (wearables/smartphones) is needed. © 2018 Elsevier B.V.