A network analysis of rest-activity rhythms in young people with emerging bipolar disorders

Mar 15, 2022Journal of affective disorders

Patterns of daily activity and rest in young people developing bipolar disorder

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Abstract

Network analysis revealed that certain rest-activity rhythm markers may be associated with different stages of bipolar disorder.

Longer sleep duration and higher levels of daytime impairment are linked to both full threshold bipolar disorder and a family history of the condition.
Regulation of circadian rhythms appears weaker in individuals with full threshold bipolar disorder compared to those with at-risk syndromes.
The study included adolescents and young adults with a mean age of 22 years, highlighting a focus on emerging bipolar disorder.
The small sample sizes may limit the detection of some associations between clinical phenotypes and rest-activity rhythm markers.

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AIMS: Actigraphy studies of individuals with bipolar disorders (BD) suggest that illness progression may be associated with a range of progressive disruptions in 24-hour rest-activity rhythms (RAR). However, those longitudinal studies were undertaken in older adults with extended histories or illness and treatment rather than young people with emerging BD. To our knowledge, this is the first study to use network modelling to examine the statistical associations between clinical phenotypes of BD and different subsets of RAR markers.

METHODS: This study of adolescents and young adults (mean age 22 years; 69% female) uses network modelling to examine which self-rated or actigraphic markers of RAR are more strongly associated with full threshold BD (referred to as Stage 2; N = 15) compared with BD-at risk syndromes (subthreshold presentations referred to as Stage 1; N = 25).

RESULTS: Network analysis demonstrated that some RAR are associated with both stage of BD and a family history of BD (such as longer sleep duration and higher levels of daytime impairment). Markers of circadian rhythmicity indicated that regulation of this system is weaker in Stage 2 compared with Stage 1 of BD.

LIMITATIONS: The small subgroup samples may have undermined the ability to detect some associations between phenotypes and RAR.

CONCLUSIONS: Network modelling may offer a useful strategy for visualizing and analysing patterns of association between RAR and clinical phenotypes defined by stage of illness, familial loading or symptom profile. This could prove useful in understanding the underlying pathophysiology of sleep-wake cycle and circadian rhythm disturbances in BD.

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A network analysis of rest-activity rhythms in young people with emerging bipolar disorders

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