Background: Bipolar disorder presents with significant phenotypic heterogeneity. The aim of this study was to investigate whether bipolar disorder, type I (BDI) subjects could be meaningfully classified into homogeneous groups according to activity, sleep, and circadian characteristics using latent profile analysis (LPA). We hypothesized that distinct BDI sub-groups would be identified based primarily on circadian-associated markers. Materials and methods: 105 individuals with BDI were included in the study. Seventeen activity, sleep, and circadian characteristics were assessed via actigraphy and clinical assessments. LPA was conducted to stratify our sample into homogenous sub-groups. Differences between groups on demographic, clinical, activity, sleep, and circadian characteristics were explored. Results: Two distinct groups were identified, a High Chronobiological Disturbance group (HCD) (56%, N = 59) and a Low Chronobiological Disturbance group (LCD) (41%; N = 46). Circadian variables were the defining characteristics in sub-group determination. Large effect sizes and magnitudes of association were noted in circadian variables between HCD and LCD sub-groups. Several circadian rhythm variables accounted for a large percentage of the variance between HCD and LCD sub-groups. No differences were noted between sub-groups on demographic characteristics and the psychiatric medications currently in use. Mood state did not significantly impact sub-group differences. Limitations: The protocol was cross-sectional in design. Longitudinal studies are required to determine the stability of the identified sub-groups. Conclusion: LPA was able to identify sub-groups in BDI with circadian variables being the most distinguishing factors in determining sub-group class membership. Future research should explore the role that circadian characteristics can play in defining sub-phenotypes of bipolar disorder.
All Science Journal Classification (ASJC) codes
- Clinical Psychology
- Psychiatry and Mental health