An ecological study of objective rest–activity markers of lithium response in bipolar-I-disorder

Abstract

Background Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest–activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR). Methods Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR). Results Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06). Conclusions To our knowledge, this is the largest actigraphy study of rest–activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups.

Chronotypes and circadian rest–activity rhythms in bipolar disorders: a meta‐analysis of self‐ and observer rating scales

“…[14][15][16][17] Furthermore, circadian markers associated with fragmentation, variability, amount and/or amplitude of day-and night-time activity may discriminate good from poor lithium responders. 18 The above findings support the potential value of assessing and monitoring CRAR in BD. However, laboratory assessments and mobile devices collating objective data are primarily employed in research rather than day-to-day clinical settings.…”

“…More recently, research has explored circadian patterns of motor activity as estimated by phase, amplitude, intradaily stability and/or interdaily variability of activity and these actigraphy markers of CRAR were suggested to discriminate BD cases from controls 14‐17 . Furthermore, circadian markers associated with fragmentation, variability, amount and/or amplitude of day‐ and night‐time activity may discriminate good from poor lithium responders 18 …”

Toward a Digital Future in Bipolar Disorder Assessment: A Systematic Review of Disruptions in the Rest-Activity Cycle as Measured by Actigraphy

“…When investigating the response to lithium, a long-standing mood-stabilizing pharmacological treatment for BD, individuals who responded well as assessed by the Retrospective Assessment of Response to Lithium Scale (the Alda scale) were also found to have more regular rest-activity patterns following treatment, as measured by IV and RA ( 107 ). Further, when using principal components analysis to classify lithium responders based on their actigraphy parameters, the same investigative group ( 108 ) found that circadian rhythmicity markers involving regularity and stability in patterns (RA, IV, IS, as well as M 10 activity) were able to correctly classify 64% of BD cases as good responders as determined by the Alda scale.…”

“…Disruptions in rest-activity patterns are shown to persist during euthymia [e.g., ( 14 , 16 , 89 )] and there is preliminary evidence that distinct patterns may differentiate BD from other major mood and psychotic disorders, and within subtypes of BD ( 7 , 69 , 81 ). Both pharmacological and non-pharmacological therapies have demonstrated rest-activity pattern stabilization associated with improvements in mood symptoms [e.g., ( 107 , 113 )]. However, the mechanisms by which these occur are yet to be fully uncovered.…”

Misunderstanding precision psychiatry

“…Luckily enough, though, the mind-brain problem does not need to be solved to advance in precision psychiatry. Pharmacogenetics (Vilches, Tuson, Vieta, Álvarez, & Espadaler, 2019), behavioral biomarkers (Scott, Hennion, Meyrel, Bellivier, & Etain, 2020) or mHealth (Hidalgo-Mazzei et al, 2018), for instance, are areas of precision psychiatry that do not rely on deciphering the biology of mental disorders and still can lead to more precise and personalized treatments.…”