Substance use disorder (SUD) is associated with disruptions in circadian rhythms. The circadian transcription factor neuronal PAS domain protein 2 (NPAS2) is enriched in reward-related brain regions and regulates reward, but its role in SU is unclear. To examine the role of NPAS2 in drug taking, we measured intravenous cocaine self-administration (acquisition, dose-response, progressive ratio, extinction, cue-induced reinstatement) in wild-type (WT) and Npas2 mutant mice at different times of day. In the light (inactive) phase, cocaine self-administration, reinforcement, motivation and extinction responding were increased in all Npas2 mutants. Sex differences emerged during the dark (active) phase with Npas2 mutation increasing self-administration, extinction responding, and reinstatement only in females as well as reinforcement and motivation in males and females. To determine whether circulating hormones are driving these sex differences, we ovariectomized WT and Npas2 mutant females and confirmed that unlike sham controls, ovariectomized mutant mice showed no increase in self-administration. To identify whether striatal brain regions are activated in Npas2 mutant females, we measured cocaine-induced DFosB expression. Relative to WT, DFosB expression was increased in D11 neurons in the nucleus accumbens (NAc) core and dorsolateral (DLS) striatum in Npas2 mutant females after dark phase self-administration. We also identified potential target genes that may underlie the behavioral responses to cocaine in Npas2 mutant females. These results suggest NPAS2 regulates reward and activity in specific striatal regions in a sex and time of day (TOD)-specific manner. Striatal activation could be augmented by circulating sex hormones, leading to an increased effect of Npas2 mutation in females.

Individuals suffering from mood and anxiety disorders often show significant disturbances in sleep and circadian rhythms. Animal studies indicate that circadian rhythm disruption can cause increased depressive- and anxiety-like behavior, but the underlying mechanisms are unclear. One potential mechanism to explain how circadian rhythms are contributing to mood and anxiety disorders is through dysregulation of the suprachiasmatic nucleus (SCN) of the hypothalamus, known as the “central pacemaker.” To investigate the role of the SCN in regulating depressive- and anxiety-like behavior in mice, we chronically manipulated the neural activity of the SCN using two optogenetic stimulation paradigms. As expected, chronic stimulation of the SCN late in the active phase (circadian time 21, CT21) resulted in a shortened period and dampened amplitude of homecage activity rhythms. We also repeatedly stimulated the SCN at unpredictable times during the active phase of mice when SCN firing rates are normally low. This resulted in dampened, fragmented, and unstable homecage activity rhythms. In both chronic SCN optogenetic stimulation paradigms, dampened homecage activity rhythms (decreased amplitude) were directly correlated with increased measures of anxiety-like behavior. In contrast, we only observed a correlation between behavioral despair and homecage activity amplitude in mice stimulated at CT21. Surprisingly, the change in period of homecage activity rhythms was not directly associated with anxiety- or depressive-like behavior. Finally, to determine if anxiety-like behavior is affected during a single SCN stimulation session, we acutely stimulated the SCN in the active phase (zeitgeber time 14-16, ZT14-16) during behavioral testing. Unexpectedly this also resulted in increased anxiety-like behavior. Taken together, these results indicate that SCN-mediated dampening of rhythms is directly correlated with increased anxiety-like behavior. This work is an important step in understanding how specific SCN neural activity disruptions affect depressive- and anxiety-related behavior.

Summary Circadian oscillations of gene expression regulates daily physiological processes, and their disruption is linked to many diseases. Circadian rhythms can be disrupted in a variety of ways, including differential phase, amplitude, and rhythm fitness. Although many differential circadian biomarker detection methods have been proposed, a workflow for systematic detection of multifaceted differential circadian characteristics with accurate false positive control is not currently available. We propose a comprehensive and interactive pipeline to capture the multifaceted characteristics of differentially rhythmic biomarkers. Analysis outputs are accompanied by informative visualization and interactive exploration. The workflow is demonstrated in multiple case studies and is extensible to general omics applications. Availability and Implementation R package, Shiny app and source code are available in Github (https://github.com/DiffCircaPipeline) and Zenodo (https://doi.org/10.5281/zenodo.7507989) Supplementary Supplementary data are available at Bioinformatics online.

No abstract