Does circadian dysrhythmia drive the switch into high- or low-activation states in bipolar I disorder?

Early warning signals observed in motor activity preceding mood state change in bipolar disorder

INTRODUCTION

Alterations in motor activity are well-established symptoms of bipolar disorder, and time series of motor activity can be considered complex dynamical systems. In such systems, early warning signals (EWS) occur in a critical transition period preceding a sudden shift (tipping point) in the system. EWS are statistical observations occurring due to a system's declining ability to maintain homeostasis when approaching a tipping point. The aim was to identify critical transition periods preceding bipolar mood state changes.

METHODS

Participants with a validated bipolar diagnosis were included to a one-year follow-up study, with repeated assessments of the participants' mood. Motor activity was recorded continuously by a wrist-worn actigraph. Participants assessed to have relapsed during follow-up were analyzed. Recognized EWS features were extracted from the motor activity data and analyzed by an unsupervised change point detection algorithm, capable of processing multi-dimensional data and developed to identify when the statistical property of a time series changes.

RESULTS

Of 49 participants, four depressive and four hypomanic/manic relapses among six individuals occurred, recording actigraphy for 23.8 ± 0.2 h/day, for 39.8 ± 4.6 days. The algorithm detected change points in the time series and identified critical transition periods spanning 13.5 ± 7.2 days. For depressions 11.4 ± 1.8, and hypomania/mania 15.6 ± 10.2 days.

CONCLUSION

The change point detection algorithm seems capable of recognizing impending mood episodes in continuous flowing data streams. Hence, we present an innovative method for forecasting approaching relapses to improve the clinical management of bipolar disorder.

Evening chronotypes with depression report poorer outcomes of SSRIs: A survey-based study of self-ratings

BACKGROUND

Preliminary evidence suggests evening chronotype relates to poorer efficacy of selective-serotonin reuptake inhibitors (SSRIs). It is unknown whether this is specific to particular medications, self-rated chronotype, or efficacy.

METHODS

In the Australian Genetics of Depression Study (N=15,108; 75% female; 18-90 years; 68% with ≥1 other lifetime diagnosis), a survey assessed experiences with 10 antidepressants and the reduced Morningness-Evening Questionnaire; a chronotype polygenic score (PGS) was calculated. Age- and sex-adjusted regression models (Bonferroni-corrected) estimated associations among antidepressants variables ("how well the antidepressant worked" [efficacy], duration of symptom improvement, side effects, discontinuation due to side effects) and self-rated and genetic chronotypes.

RESULTS

The chronotype-PGS explained 4% of the variance in self-rated chronotype (r=0.21). Higher self-rated eveningness was associated with poorer efficacy of escitalopram (OR=1.04; 95% CI 1.02-1.06; p=0.000035), fluoxetine (OR=1.03; 95% CI 1.01-1.05; p=0.001), sertraline (OR=1.02; 95% CI 1.01-1.04; p=0.0008), and desvenlafaxine (OR=1.03; 95% CI 1.01-1.05; p=0.004), and a profile of increased side effects (80% of those recorded; ORs=0.93-0.98), with 'difficulty getting to sleep' most likely. Self-rated chronotype was not related to duration of improvement or discontinuation due to side effects. The chronotype-PGS was only associated with suicidal thoughts and attempted suicide (self-reported). While our measures are imperfect, and not of circadian phase under controlled conditions, the model coefficients suggest that dysregulation of phenotypic chronotype relative to its genetic proxy was driving relationships with antidepressant outcomes.

CONCLUSIONS

The idea that variation in circadian factors influences antidepressant responses was supported and encourages exploration of circadian mechanisms of depressive disorders and antidepressant treatments.

Dynamic modelling of chronotype and hypo/manic and depressive symptoms in young people with emerging mental disorders

There is significant interest in the possible influence of chronotype on clinical states in young people with emerging mental disorders. We apply a dynamic approach (bivariate latent change score modelling) to examine the possible prospective influence of chronotype on depressive and hypo/manic symptoms in a youth cohort with predominantly depressive, bipolar, and psychotic disorders (N = 118; 14-30-years), who completed a baseline and follow-up assessment of these constructs (mean interval = 1.8-years). Our primary hypotheses were that greater baseline eveningness would predict increases in depressive but not hypo/manic symptoms. We found moderate to strong autoregressive effects for chronotype (β = -0.447 to -0.448, p < 0.001), depressive (β = -0.650, p < 0.001) and hypo/manic symptoms (β = -0.819, p < 0.001). Against our predictions, baseline chronotypes did not predict change in depressive (β = -0.016, p = 0.810) or hypo/manic symptoms (β = 0.077, p = 0.104). Similarly, the change in chronotype did not correlate with the change in depressive symptoms (β = -0.096, p = 0.295) nor did the change in chronotype and the change in hypo/manic symptoms (β = -0.166, p = 0.070). These data suggest that chronotypes may have low utility for predicting future hypo/manic and depressive symptoms in the short term, or that more frequent assessments over longer periods are needed to observe these associations. Future studies should test whether other circadian phenotypes (e.g. sleep-wake variability) are better indicators of illness course.