A recent study published in the Proceedings of the National Academy of Sciences finds links between sleeping patterns, circadian rhythms, bipolar disorder and specific phenotypes.
Bipolar Disorder previously referred to as manic depression, is characterized by periods of hyperactivity followed by bouts of depression.
The manic phase can include feelings of creativity, racing thoughts and delusions of grandeur. The lows might involve lethargy and feelings of worthlessness.
According to the National Institute of Mental Health, around 2.6% of the adult population of America has experienced bipolar disorder in the last 12 months.
Despite the large number of individuals with the condition, the exact causes of bipolar, as with many other mental disorders, are not known. Genetics, however, do seem to be of importance; bipolar disorder is known to run in families.
Sleep and bipolar disorder
Sleep and circadian rhythms are also known to play a part in bipolar disorder. Manic phases generally see the individual sleeping less; conversely, during depressive periods, sleep is often more prevalent.
Some researchers have concluded that sleep might be a factor in bipolar relapses, or perhaps an early warning sign of bipolar events on the horizon.
The current research, carried out by Dr. Joseph Takahashi at the University of Texas Southwestern Medical Center and the University of California-Los Angeles, takes a deeper look at the familial component of bipolar disorder and its specific effects on sleep patterns.
Twin studies have already shown that there is a genetic component to some sleep parameters. For instance, the quantity of rapid eye movement (REM) and delta sleep that an individual has during a night’s sleep is more similar in people who are more genetically alike.
Dr. Takahashi’s study looks to bring the genetics of sleep research and the circadian facets of bipolar disorder into the same frame.
The investigation focused on 558 members of 26 families from Central Valley, Costa Rica, and Antioquia, Colombia. This group consisted of 136 individuals with bipolar disorder and 422 of their relatives without the disorder.
Each participant wore an accelerometer on their wrist for 14 days. The data from these devices allowed the research team to define their sleep-wake cycles and the amount of general activity each participant undertook.
Dr. Takahashi says:
“We were able to identify 13 sleep and activity measures, most of which are inherited, that correlated with whether an individual had bipolar disorder. In addition, we were able to trace some of these traits to a specific chromosome.”
The study showed that, in general, individuals with bipolar disorder were less active while they were awake, they went to sleep later and slept for longer than non-bipolar individuals.
Circadian differences in bipolar disorder
Below is a list of the specific sleep and circadian phenotypes that were found to significantly vary between those with bipolar disorder and those without:
- Mean awake duration: average length of time spent awake per day
- Amplitude: a measure of the strength of an individual’s circadian rhythm
- Hill acrophase: time of day at which activity peaked
- Interdaily stability: the degree of variation in levels of activity each day
- Interdaily variability: a measure of the fragmentation of circadian rhythm
- Median activity: average amount of activity per day
- Relative amplitude: the difference between the least and the most intense periods of activity across 24 hours
- Mean length of sleep bouts during the sleep period: average amount of time spent in each bout of sleep during the night
- Mean number of sleep bouts during awake period: average length of naps during the day
- Time of sleep offset: time of awakening in the morning
- Mean total minutes scored awake: average time spent awake per day
- WASO: total minutes spent awake after the onset of sleep.
The study is the first to link specific phenotypes to the etiology of bipolar disorder. The hope is that these findings will help unravel the mechanisms of the disease and potentially provide novel targets for future pharmaceutical interventions.