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Sleep information as an early predictor of depressive disorders

· 7 min read

Changes in sleep-wake mechanisms such as the manifestation of insomnia and/or hypersomnia is a common symptoms present in a few depressive disorders.


According to the Diagnostic and Statistical Manual of Mental Health 5th edition (DSM-5; American Psychiatric Association, 2013), depressive disorders refer to a category of mood affective disorders that comprise disorders such as major depressive disorder, seasonal affective disorder, persistent depressive disorder, etc. All the disorders under this category center around an individual’s mood state (e.g. presence of sadness, emptiness, or irritation), and specific cognitive and somatic changes (American Psychiatric Association, 2013) that causes them distress and hinders their ability to function in everyday life.

While there are huge variations within the category of depressive disorders, there are some symptoms that overlap across the different depressive disorders. According to the DSM-5, changes in sleep-wake mechanisms such as the manifestation of insomnia and/or hypersomnia is a common symptoms present in a few depressive disorders (American Psychiatric Association, 2013). Previous studies have suggested that sleep disturbances are present in about 90% of individuals with depression (Soehner et al., 2014). Tsuno et al. (2005) found that individuals with depression experience a variety of sleep disturbances such as decreased deep sleep, decreased rapid-eye movement (REM) stage sleep latency, and increases in the proportion of the time spent in REM in the early half of the night. It was also suggested that individuals with depression are more likely to experience impaired sleep continuity and duration (Tsuno, Bassett, & Richie, 2005; Franzen & Buysse, 2008), may have problems initiating sleep (Franzen & Buysse, 2008), and may experience early morning-awakenings (Franzen & Buysse, 2008).

Insomnia and Hypersomnia in Depression

The sleep problems experienced during depression can be grouped under two broad sleep disorder categories: insomnia and hypersomnia. Insomnia is a sleep disorder that causes an individual to have trouble falling asleep and/or trouble to stay asleep at night. Whereas, hypersomnia is a sleep disorder that causes an individual to have trouble staying awake during the day despite getting a night’s sleep, excessive daytime napping, and increases in night-time wakefulness. About 75% of the individuals that are diagnosed with some form of depression suffer from insomnia (Sleep Foundation, 2022). About 16-20% of individuals with depression (Tsuno et al., 2005) and 10-50% of individuals with other mood disorders suffer from hypersomnia (Kaplan et al., 2009; Geoffrey et al., 2018).

Some studies have suggested that insomnia and hypersomnia may manifest prior to the manifestation of depressive disorders (Riemann & Voderholzer, 2003; Taylor et al., 2003; Lustberg & Reynolds III, 2003; Fava, 2004; Vargas & Perlis, 2020), making sleep abnormalities an important predictor of depressive disorder in various different demographic population groups. With regards to specific depressive disorders, previous studies have suggested that insomnia complains are one of the most common during the diagnosis of major depressive disorder (Geoffrey et al., 2018) but hypersomnia appears to be more prevalent in individuals with bipolar disorder (Murru et al., 2019), and seasonal affective disorder during winter (Tsuno et al., 2005; Kaplan et al., 2009). The co-occurrence of hypersomnia and insomnia is more likely to be associated with a diagnosis of bipolar disorder, panic disorders, and PTSD (Murru et al., 2019; Geoffrey et al., 2018).

During the treatment of depressive disorders, sleep problems tend to improve and eventually disappear (Lustberg & Reynolds III, 2003), however, sleep problems especially insomnia tend to manifest again prior to a relapse (Lustberg & Reynolds III, 2003; Murru et al., 2019; Kaplan et al., 2009; Vargas & Perlis, 2020). An improvement in sleep during the treatment period positively indicated an improvement in the overall prognosis of depressive disorders (Vargas & Perlis, 2020). Therefore, monitoring sleep throughout the treatment duration and during follow-up periods may prove beneficial to the individual and the clinician as the continual or re-emergence of sleep abnormalities may be an important indicator of worsening symptoms and relapse, respectively.

Early detection of depression via sleep sensors

As sleep disturbances are important predictors of onset and relapse of depressive disorders and other related psychiatric disorders (Murru et al., 2019; Kaplan et al., 2009; Vargas & Perlis, 2020), monitoring sleep may allow an individual and clinician to seek treatment to control sleep issue, and so, avoid onset and/or re-emergence of the depression. Since sleep problems may manifest as early as 1-3 years before depressive disorder onset (Riemann & Voderholzer, 2003; Taylor et al., 2003; Lustberg & Reynolds III, 2003; Fava, 2004; Vargas & Perlis, 2020), early diagnosis and treatment of insomnia and/or hypersomnia may allow for a better treatment outcome through preventative and/or through early-interventions, potentially preventing the onset of major depressive disorder (or other depressive disorders) in at-risk individuals (Franzen & Buysse, 2008; Vargas & Perlis, 2020). Monitoring sleep after the treatment period may help the individual and the clinician to detect potential relapse and may provide added reassurance.

Digital markers could potentially provide a solution by using machine learning and behavioral sleep data from smartphones and other wearables to predict mental health issues and outcomes, objectively. The ubiquitous nature of smartphones and other wearables could be used by mental health service providers to passively collect sleep data to measure for any sleep abnormality that may be present to determine if an individual is at risk of developing depressive or other psychiatric disorders. Passively collected sleep data would allow an individual to monitor their sleep data and be aware of any potential risks of depression onset or relapse. Digital markers could be used as an early-detection assessment method but also could be used in the post-treatment follow-up care plan. So, digital markers could be important for the individual with the underlying mental health concern but can also be beneficial as a tool for the clinician.

Future Direction

The emerging digital health field may wish to further explore the differences in specific sleep issues in the different psychiatric disorders using smartphone and/or wearable sleep sensors. As mentioned above, there are differences in sleep abnormalities for individuals with major depressive disorder (Geoffrey et al., 2018), seasonal affective disorder (Tsuno et al., 2005; Kaplan et al., 2009), and other psychiatric disorders (Murru et al., 2019; Geoffrey et al., 2018). It may be useful to differentiate between mental health issues based on sleep data obtained from various passive sleep sensors to improve early-detecting assessment methods and follow-up care plans.


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