The Role of Circadian Rhythm in Mood Disorders

Post by Rebecca Hill

How does the circadian rhythm impact mood?

Circadian rhythms are physiological mechanisms that allow humans and many other animals to respond to light and have regular periods of both activity and restful sleep. Circadian rhythms are coordinated by an area in the hypothalamus called the suprachiasmatic nucleus (SCN), which receives direct light input from the retina (Reppert & Weaver, 2001). There is now a growing body of evidence that mood disorders, often diagnosed by abnormal sleep patterns, are associated with disrupted circadian rhythms. These studies have contributed to our understanding of mood disorders and how they can be treated, showing that therapeutic treatments that target circadian mechanisms can often help lessen the symptoms of mood disorders. 

Some of the most common mood disorders include seasonal affective disorder (SAD), major depressive disorder (MDD), and bipolar disorder (BD), with each affecting between 2.8-5% of adults. A core diagnostic symptom of all mood disorders is abnormal sleep/wake patterns. Symptoms for SAD usually start during the change from fall to winter when the daylight hours quickly become shorter (Melrose, 2015). Similarly, manic and depressive episodes of BD are often triggered by seasonal changes (Geoffroy et al., 2014). Patients with BD usually have their sleep/wake patterns disrupted by manic and depressive episodes, which are also in turn triggered by changes to sleep patterns (McCarthy et al., 2022; Malkoff-Schwartz et al., 2000). In MDD, patients cycle through depressive moods throughout the day, with the worst symptoms usually occurring in the early morning (Wirz-Justice, 2022).

The prevalence of depressive mood disorders is increasing, and this could be linked to disrupted sleep driven by the uptick in the amounts of artificial light we are exposed to from phones, computers, and televisions, especially at night (Hidaka, 2012). In addition to this, shift work is common, and forces workers to be awake when their bodies expect to be asleep. This disrupts natural circadian rhythms and may also contribute to the increasing prevalence of mood disorder diagnoses (Boivin et al., 2022).

Neurons signal to adapt to changes in daylight

Midbrain dopamine neurons have been found to be linked to symptoms of depression. Rats exposed to short light days had more dopamine neurons in the hypothalamus that, when damaged, started presenting depression-like behavior (Dulcis et al., 2013). The neurons in the SCN signal at different rates during the summer and winter months, so individuals with SAD may have a SCN that can’t adapt to different seasonal cues (VanderLeest et al., 2007). Manic-like behavior, like that seen in patients with BD, was found in mice with optogenetic stimulation of dopamine neurons, but only at certain times of the day (Sidor et al., 2015). Together, research findings like these indicate that neurons are signaling changes in daylight throughout the seasons, and abnormal signaling could result in the symptoms seen in mood disorders.

Melatonin dysfunction contributes to mood disorders

Melatonin is a hormone released by the pineal gland to indicate darkness and facilitate sleep, meaning more melatonin is released during shorter days. Patients with SAD sometimes have an overproduction of melatonin during the winter and also produce it later in the day than normal, leading to fatigue during the daytime (Lewy et al., 2006; Srinivasan et al., 2006). Melatonin is also produced less, and at inappropriate times of the day by patients with MDD (Pandi-Perumal et al., 2020). Further, individuals with BD are hypersensitive to light at night, which can lead to the suppression of melatonin, and a delay in sleep.

How can we treat these mood disorder symptoms?

Bright-light therapy is the most widely used treatment for SAD. This treatment is typically used in the early morning, since this is the most effective timing window, however, the optimal timing and “dose” of light can vary for each person (Partonen, 1994). Bright-light therapy might work, especially if used in the morning, because it decreases the amount of melatonin being produced at inappropriate times during the day (West et al., 2011), and gives our bodies a strong morning light cue.

Antidepressant medications such as selective serotonin reuptake inhibitors (SSRIs) have also shown promise in helping to reset signaling in the SCN to correct circadian rhythms and decrease depression symptoms (Sprouse et al., 2006). Patients with BD are often treated with lithium, which when used in subjects with shorter circadian periods will lengthen the circadian period, correcting it to the natural 24-hour cycle (Mishra et al., 2021).

What’s next?

For proper mood regulation, the physiological circadian systems must be able to adapt to changes in daylight across the seasons. Individuals with an unstable sleep/wake cycle are more likely to develop mood disorders. Based on recent research, the stabilization of circadian rhythms can often treat the symptoms of mood disorders. Treatments such as bright-light therapy, melatonin, and SSRIs, when personalized to the individual, can greatly improve the outlook for patients with depressive mood disorders. 

References +

Boivin, D. B., Boudreau, P., & Kosmadopoulos, A. (2022). Disturbance of the circadian system in shift work and its health impact. Journal of biological rhythms, 37(1), 3-28.

Dulcis, D., Jamshidi, P., Leutgeb, S., & Spitzer, N. C. (2013). Neurotransmitter switching in the adult brain regulates behavior. science, 340(6131), 449-453.

Geoffroy, P. A., Bellivier, F., Scott, J., & Etain, B. (2014). Seasonality and bipolar disorder: a systematic review, from admission rates to seasonality of symptoms. Journal of Affective Disorders, 168, 210-223.

Hidaka, B. H. (2012). Depression as a disease of modernity: explanations for increasing prevalence. Journal of affective disorders, 140(3), 205-214.

Lewy, A. J., Lefler, B. J., Emens, J. S., & Bauer, V. K. (2006). The circadian basis of winter depression. Proceedings of the National Academy of Sciences, 103(19), 7414-7419.

Malkoff-Schwartz, S., Frank, E., Anderson, B. P., Hlastala, S. A., Luther, J. F., Sherrill, J. T., ... & Kupfer, D. J. (2000). Social rhythm disruption and stressful life events in the onset of bipolar and unipolar episodes. Psychological medicine, 30(5), 1005-1016.

McCarthy, M. J., Gottlieb, J. F., Gonzalez, R., McClung, C. A., Alloy, L. B., Cain, S., ... & Murray, G. (2022). Neurobiological and behavioral mechanisms of circadian rhythm disruption in bipolar disorder: A critical multi‐disciplinary literature review and agenda for future research from the ISBD task force on chronobiology. Bipolar disorders, 24(3), 232-263.

Melrose, S. (2015). Seasonal affective disorder: an overview of assessment and treatment approaches. Depression research and treatment, 2015.

Mishra, H. K., Ying, N. M., Luis, A., Wei, H., Nguyen, M., Nakhla, T., ... & McCarthy, M. J. (2021). Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response: preliminary studies. Molecular psychiatry, 26(7), 3383-3394.

Pandi-Perumal, S. R., Monti, J. M., Burman, D., Karthikeyan, R., BaHammam, A. S., Spence, D. W., ... & Narashimhan, M. (2020). Clarifying the role of sleep in depression: A narrative review. Psychiatry research, 291, 113239.

Partonen, T. (1994). Effects of morning light treatment on subjective sleepiness and mood in winter depression. Journal of affective disorders, 30(2), 99-108.

Reppert, S. M., & Weaver, D. R. (2001). Molecular analysis of mammalian circadian rhythms. Annual review of physiology, 63(1), 647-676.

Sidor, M. M., Spencer, S. M., Dzirasa, K., Parekh, P. K., Tye, K. M., Warden, M. R., ... & McClung, C. A. (2015). Daytime spikes in dopaminergic activity drive rapid mood-cycling in mice. Molecular psychiatry, 20(11), 1406-1419.

Sprouse, J., Braselton, J., & Reynolds, L. (2006). Fluoxetine modulates the circadian biological clock via phase advances of suprachiasmatic nucleus neuronal firing. Biological psychiatry, 60(8), 896-899.

Srinivasan, V., Smits, M., Spence, W., Lowe, A. D., Kayumov, L., Pandi-Perumal, S. R., ... & Cardinali, D. P. (2006). Melatonin in mood disorders. The World Journal of Biological Psychiatry, 7(3), 138-151.

VanderLeest, H. T., Houben, T., Michel, S., Deboer, T., Albus, H., Vansteensel, M. J., ... & Meijer, J. H. (2007). Seasonal encoding by the circadian pacemaker of the SCN. Current Biology, 17(5), 468-473.

West, K. E., Jablonski, M. R., Warfield, B., Cecil, K. S., James, M., Ayers, M. A., ... & Brainard, G. C. (2011). Blue light from light-emitting diodes elicits a dose-dependent suppression of melatonin in humans. Journal of applied physiology.

Wirz-Justice, A. (2022). Diurnal variation of depressive symptoms. Dialogues in clinical neuroscience.

­Music-Induced Emotions Affect How We Encode Memories

Post by Anastasia Sares

The takeaway

Emotion and memory are tightly linked, but it is hard to measure continuous fluctuations in emotional states reliably in the lab. This work used music to reliably induce emotions across time and examined how transitions between different emotional states affect memory.

What's the science?

We are constantly processing the continuous stream of experience that happens in life, placing similar information into different “episodes” so that we can store them efficiently in memory. Transitioning into new contexts or situations can lead to uncertainty, like walking out of a building or changing conversation partners at a party, for example. Therefore, we are generally more vigilant during these times, paying more attention to what is new and having better memory for individual items. On the other hand, within an episode, we are better at remembering relationships between different items and the order of information, such as the numbers of the rooms we pass in a hallway or the order of topics in a conversation.

Most of the above examples involve external cues to signal the boundaries between adjacent events. But we also have an inner life, and we can transition between states of mind just as easily as we walk through doors or change conversation partners. In particular, we often transition between different emotional states over time. This week in Nature Communications, McClay and colleagues used music to induce different emotional states and show how fluctuations in these emotional states affect memory formation.

How did they do it?

The authors hired trained film score composers to create emotional musical pieces (choosing from joyous, calm, sad, and anxious), with each piece having three distinct sections with different emotions. These pieces were meant to induce a range of emotions according to the circumplex model of emotion, which holds that emotions can be defined along two main dimensions: arousal and valence. Arousal refers to the energy level of an emotion: high-energy emotions include joy and anxiousness, while low-energy emotions include sadness and calm. Valence refers to the positive or negative quality of an emotion: positive valence emotions include happiness and calm, while negative valence emotions include anxiousness and sadness.

Participants first listened to the pieces in the background while trying to memorize a series of neutral images. At test time, they were presented with two objects and asked which one came first, and also how far apart the objects were in time. Finally, the participants were asked to rate the emotions they felt during the musical pieces using an “Emotional Compass”, a circle that captures a wide range of emotional valence and arousal levels. Participants rated their felt emotions in real-time, moving the mouse around on the Compass while re-listening to the musical pieces. In this way, the authors could extract measures of both the valence and the arousal levels participants experienced at each point in time and could then relate this to their memory performance. They also had a separate group of participants identify musical transitions, where the pitch or complexity changed significantly, so they could factor out the influence of these external sensory boundaries in their analyses. 

What did they find?

When two images were separated by a significant emotional transition, people experienced “time dilation” – in other words, they judged the images to be further apart in time than they actually were. Participants also had worse memory for the order of those images. Images that were shown at a boundary transition were better preserved in long-term memory overall (this was tested one day later). These effects are typical of the memory effects seen in previous studies, showing that our experience can be segmented according to our internal states just as much as our external context.

On the other hand, a large shift towards more positive emotions led to item pairs being judged as closer in time (i.e., “time compression”) and people remembered the order of those images better. High-arousal positive emotions also boosted long-term memory for accompanying items: participants could better identify which items were presented as well as when those items were encountered during the sequence. These findings indicate that positive emotions can help to fuse things together in memory, while either being in or shifting towards more negative emotional contexts may instead contribute to memory segmentation and worse memory for timing.

What's the impact?

This work shows that internal emotional states, especially emotional valence, can separate events in memory just like external changes in place and time. It also demonstrates that music is a useful tool for studying emotion in a continuous context in a realistic and reliable way.

Converting Microglia to Neurons Has Therapeutic Potential Following Stroke

Post by Laura Maile

The takeaway

In adult mammals, most neurons cannot proliferate, which means that neuronal loss following stroke and other brain injuries is irreversible. Microglia, the immune cells of the brain, maintain their capacity to divide and can be converted into neurons in mice with stroke, leading to improved neurological function. 

What's the science?

Neuronal loss is one of the major pathological effects of stroke that contributes to disability and poor health outcomes. The mammalian brain maintains limited ability for adult neurogenesis, adding to the negative effects of neuronal loss due to stroke and other brain injuries. The conversion of other cell types to neurons at the site of injury therefore presents a therapeutic opportunity that could improve functional recovery. Some researchers have had success in converting astrocytes to neurons, leading to functional improvement. In the most common cause of stroke, however, both astrocytes and neurons are depleted at the site of injury while microglia and macrophages infiltrate the injured area, making them a better target for conversion following ischemic stroke.  This week in PNAS, Irie and colleagues converted microglia and macrophages into neurons in the striatum of stroke mice using a single transcription factor and measured their functional improvements over time.

How did they do it?

The authors induced ischemic stroke using transient middle cerebral artery occlusion (tMCAO), and performed immunohistochemistry to analyze the lesioned area and the cell types located throughout the injured tissue. A week following stroke, they injected a virus carrying the NeuroD1 (ND1) transcription factor driven by a microglia-specific promoter into the injured brain area to convert infiltrating microglia and macrophages into neurons. Next, to determine whether the ND1-converted neurons became functionally integrated into the striatum, they used immunohistochemistry to stain striatal projection neurons in control and tMCAO mice and patch-clamp electrophysiology to record neuronal activity from these cells. To quantify how many microglia/macrophages were effectively transformed into neurons, they utilized a transgenic mouse line expressing cre-inducible diphtheria toxin receptor (DTR). By injecting a Cre virus with a microglia-specific promoter, they could permanently express DTR in microglia, and then count the number of DTR-expressing cells that became neurons at different time points. The authors then tested whether the conversion of microglia into neurons had functional outcomes on stroke recovery, by comparing multiple motor behaviors in injured and control mice. Finally, they ablated the ND1-converted neurons to examine whether these cells were responsible for functional improvements. 

What did they find?

They showed that following stroke, there is a significant neuronal loss in the striatum, and that while astrocytes remain at the border of the lesioned area, microglia and macrophages infiltrate into the core of the lesion. Two weeks following the injection of their virally packaged transcription factor, they showed a reduction in the microglial population and an increase in neuronal markers, which means that cells at the lesion site were reprogrammed from a microglial identity into a neuronal one. They also showed that when microglia were depleted prior to injection of ND1, they no longer observed the increase in neuronal cells at the lesion site, indicating it is likely mostly microglia that are successfully converted into neurons. Using immunohistochemistry, they demonstrated that striatal projection neurons, which are largely depleted in the lesioned area following tMCAO, show recovery following ND1 transduction. Their ND1-transduced cells became positive for a striatal neuron marker and showed functional activity that mimicked that of native striatal neurons.

They next found that one week after labeling microglia and initiating their conversion into neurons, very few labeled cells expressed neuronal markers, indicating they hadn’t yet converted to neurons at this early stage. At the eight week timepoint, however, a large number of the permanently labeled DTR cells also expressed striatal neuron markers and showed anatomically relevant connections with other neurons. This means that their strategy to convert microglia at the lesion site into neurons that would be integrated into the native circuitry was successful. Finally, they showed that following the conversion of microglia to neurons at the lesion site one week post-injury, mice showed improvements in multiple motor behaviors impacted by stroke. Damaging ND1-converted neurons blocked these improvements, suggesting that these newly converted neurons were responsible for the functional improvements observed. 

What's the impact?

This study is the first to show successful in vivo conversion of microglia into functional neurons following ischemic stroke in mice. This treatment, which led to improved neurological function in injured mice, demonstrates a promising therapeutic strategy for stroke and other injuries resulting in the loss of neurons.