송윤민 (KAIST, IBS)

한빛사논문

조회547

송윤민Yun Min Song

KAIST, IBS

EBioMedicine, Volume 103, May 2024, 105094 | https://doi.org/10.1016/j.ebiom.2024.105094 Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data

Yun Min Song ^a,b,g, Jaegwon Jeong^c,d,g, Aurelio A. de los Reyes V ^b,e,g, Dongju Lim^a,b, Chul-Hyun Cho ^c,d, Ji Won Yeom ^c,d, Taek Lee ^f, Jung-Been Lee ^f, Heon-Jeong Lee ^c,d, Jae Kyoung Kim ^a,b

^aDepartment of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea

^bBiomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea

^cDepartment of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea

^dChronobiology Institute, Korea University, Seoul, 02841, Republic of Korea

^eInstitute of Mathematics, University of the Philippines Diliman, Quezon City, 1101, Philippines

^fDivision of Computer Science and Engineering, Sun Moon University, Asan, 31460, Republic of Korea

^gThese authors contributed equally.

Corresponding authors: Heon-Jeong Lee, Jae Kyoung Kim

Abstract

Background: Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown.

Methods: We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method.

Findings: The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms.

Interpretation: Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively.

논문정보

형식Research article
게재일2024년 05월 (BRIC 등록일 2024-04-08)
연구진국내 연구진
분야 바이오·의료융합 > 다학제 융합/복합

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