Daytime spikes in dopaminergic activity drive rapid mood-cycling in mice
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Author(s)
Sidor, M. M.
Spencer, S. M.
Dzirasa, K.
Parekh, P. K.
Tye, Kay
Warden, M. R.
Arey, R. N.
Enwright, J. F.
Jacobsen, J. P. R.
Kumar, S.
Date Issued
January 2015
Journal
Molecular Psychiatry
Publisher
Nature Publishing Group
Citation
Sidor, M M, S M Spencer, K Dzirasa, P K Parekh, K M Tye, M R Warden, R N Arey, et al. “Daytime Spikes in Dopaminergic Activity Drive Rapid Mood-Cycling in Mice.” Molecular Psychiatry 20, no. 11 (November 2015): 1406–19.
Version
Author's final manuscript
Abstract
Disruptions in circadian rhythms and dopaminergic activity are involved in the pathophysiology of bipolar disorder, though their interaction remains unclear. Moreover, a lack of animal models that display spontaneous cycling between mood states has hindered our mechanistic understanding of mood switching. Here, we find that mice with a mutation in the circadian Clock gene (ClockΔ19) exhibit rapid mood-cycling, with a profound manic-like phenotype emerging during the day following a period of euthymia at night. Mood-cycling coincides with abnormal daytime spikes in ventral tegmental area (VTA) dopaminergic activity, tyrosine hydroxylase (TH) levels and dopamine synthesis. To determine the significance of daytime increases in VTA dopamine activity to manic behaviors, we developed a novel optogenetic stimulation paradigm that produces a sustained increase in dopamine neuronal activity and find that this induces a manic-like behavioral state. Time-dependent dampening of TH activity during the day reverses manic-related behaviors in ClockΔ19 mice. Finally, we show that CLOCK acts as a negative regulator of TH transcription, revealing a novel molecular mechanism underlying cyclic changes in mood-related behavior. Taken together, these studies have identified a mechanistic connection between circadian gene disruption and the precipitation of manic episodes in bipolar disorder.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Picower Institute for Learning and Memory
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DOI of Published Version
https://doi.org/10.1038/mp.2014.167
