0972 Rest-activity Rhythm Profiles in Major Depressive Disorder: A Cluster Analysis in Chinese Population

Introduction

Previous research has demonstrated that rest-activity rhythm (RAR) profiles, formed by individual RAR characteristics, were linked to the severity of depressive symptoms. Further investigation into RAR profiles could potentially facilitate the identification of depression and validate its role in depression. This study aimed to identify the RAR profiles in samples with and without major depressive disorder (MDD).

Methods

Actigraphy data were collected from 70 Chinese adults (34 with current MDD and 36 age- and gender-matched healthy controls) aged between 18 and 64. RAR measures were computed based on the collected 7-day actigraphy data, and a data-driven cluster analysis was performed to identify distinct RAR profiles. The associations between the actigraphy-derived RAR profiles and various psychiatric symptom/health-related measures, including anxiety and depressive symptoms, insomnia severity, fatigue, and quality of life, were examined.

Results

Two distinct groups with different RAR features (“earlier/robust” group: n = 63, 90%; “later/irregular”; n = 7, 10%) were identified from the sample using cluster analysis. The “later/irregular” group exhibited later activity onset and acrophase, along with lower levels of robustness and regularity compared to the “earlier/robust” group. Regarding psychiatric symptom/health-related measures, the “later/irregular” group displayed significantly higher levels of depressive symptoms [t(8.77) = -3.36, p <.05], insomnia severity [t(15.3) = -6.85, p <.05], fatigue [t(8.80) = -2.68, p <.05], and a higher percentage of participants with current MDD [χ2(1) = 4.30, p <.05] relative to the “earlier/robust” group. However, insignificant differences in health-related quality of life [t(7.71) = 2.27, p =.054] were found between two groups.

Conclusion

The current findings contribute further evidence on the association between RAR profiles and MDD, suggesting that RAR profiles could potentially be a biological marker for identifying depression. The observed associations between RAR profiles and other related symptoms demonstrated the utility of RAR profiles in detecting other health-related concerns. However, it is important to note that confirmatory studies with larger sample sizes and longitudinal designs are necessary to validate these findings and reveal the underlying mechanisms and temporal relationship between circadian rhythms and depression.

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