Skip to main content
Full access
Reviews and Overviews
Published Online: 1 October 2021

The Evolving Nexus of Sleep and Depression

Abstract

Sleep disturbances and depression are closely linked and share a bidirectional relationship. These interconnections can inform the pathophysiology underlying each condition. Insomnia is an established and modifiable risk factor for depression, the treatment of which offers the critical opportunity to prevent major depressive episodes, a paradigm-shifting model for psychiatry. Identification of occult sleep disorders may also improve outcomes in treatment-resistant depression. Sleep alterations and manipulations may additionally clarify the mechanisms that underlie rapid-acting antidepressant therapies. Both sleep disturbance and depression are heterogeneous processes, and evolving standards in psychiatric research that consider the transdiagnostic components of each are more likely to lead to translational progress at their nexus. Emerging tools to objectively quantify sleep and its disturbances in the home environment offer great potential to advance clinical care and research, but nascent technologies require further advances and validation prior to widespread application at the interface of sleep and depression.
It has long been appreciated that sleep disturbance and depression frequently co-occur. Recent reviews have detailed the history of sleep and depression research, from changes in sleep architecture observed in depression, including alterations in slow-wave and rapid eye movement (REM) sleep, to effects of antidepressant compounds and chronotherapeutics on sleep staging and mood (1). While great scientific progress has been made at the interface of sleep and depression, even robust findings have at times resulted in conclusions of limited translational utility. However, the potential to refine research strategies and clinical paradigms at the nexus of sleep and depression offers new and exciting trajectories that may dramatically alter the landscape of psychiatric practice.

Interconnections of Insomnia and Depression

Insomnia and depression share a bidirectional relationship, in which each separate entity can influence the course of the other (2). It is rare for patients experiencing a major depressive episode not to experience some form of sleep disturbance. Insomnia is the most common sleep complaint among those with comorbid depression, occurring in approximately 80%−90% of patients (3). Importantly, meta-analysis has demonstrated that insomnia increases the odds of developing depression roughly twofold, which is on par with the risk associated with having a first-degree relative with recurrent major depressive disorder (4, 5). Additionally, twin and genome-wide association studies have demonstrated sizable genetic overlap between insomnia and major depression (6, 7).
Given the connections between insomnia and depression both cross-sectionally and longitudinally, consideration of insomnia as a contributing factor in genetics and neuroimaging results could further advance our understanding of these heterogeneous processes (8). While relatively few studies have examined the impact of insomnia on neuroimaging findings in major depression, overlapping structural and functional abnormalities in the medial prefrontal cortex and posterior cingulate cortex within the default mode network, as well as the insula, anterior cingulate cortex, and amygdala within the salience network have separately been observed in each condition (9). In terms of structural findings, the ENIGMA (Enhancing Neuroimaging Genetics Through Meta-Analysis) depression working group recently demonstrated in 1,053 persons with major depressive disorder that more severe insomnia symptoms were associated with reduced cortical surface area, primarily in the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus (10). Notably, these associations were not observed among healthy or clinical control subjects with bipolar disorder, suggesting that these associations between surface area in frontoparietal cortical areas and insomnia are unique to depression (10). In terms of functional neuroimaging, Cheng et al. (12) analyzed data from the Human Connectome project, demonstrating that increased functional connectivity in multiple brain areas (lateral orbitofrontal cortex, dorsolateral prefrontal cortex, anterior and posterior cingulate cortices, insula, parahippocampal gyrus, hippocampus, amygdala, temporal cortex, and precuneus) was associated with both sleep quality (measured using the Pittsburgh Sleep Quality Index [11]) and depressive symptoms, suggesting a neural basis for their overlap. Drysdale et al. (13) successfully segregated treatment-resistant depression along two dimensions—one predicting anhedonia symptoms based on frontostriatal and orbitofrontal connectivity, the other predicting anxiety and insomnia based on connectivity within the amygdala, ventral hippocampus, ventral striatum, and lateral prefrontal cortex. While patterns of clinical symptoms prior to treatment were only modestly associated with therapeutic effects of transcranial magnetic stimulation applied at the dorsomedial prefrontal cortex, subgroups that accounted for these connectivity patterns were better able to predict treatment response (13).
An important limitation of nearly all neuroimaging approaches that are used to study insomnia and depression is that they evaluate the waking brain. Thus, quantitative measures acquired during the sleep period, such as EEG, are more likely to provide insights into brain changes that may co-occur in insomnia and depression. While increased high-frequency EEG activity during sleep has been generally reported in insomnia disorder (14), such sleep EEG changes have typically not been described using sleep spectral analysis in persons with major depression and comorbid insomnia (15, 16). In this instance, the use of standard EEG montages that have limited spatial resolution may be a significant barrier in this line of inquiry, particularly since preliminary evidence has demonstrated that local alpha activity persists in sensory and sensorimotor cortical areas in persons with insomnia, even in the deepest stages of non-REM sleep (17). Thus, the use of high-density EEG arrays during sleep has significant promise to advance research on sleep and depression, as has been the case for other psychiatric disorders (18, 19).
From a more pragmatic standpoint, it is important to know whether treatment of insomnia occurring in the context of a depressive episode enables therapeutic effects beyond the improvement of sleep symptoms. Two earlier randomized controlled trials focused on nonbenzodiazepine Z-drugs (placebo versus active compound) with open-label use of specific serotonin reuptake inhibitors (SSRIs) (20, 21). While both studies demonstrated a significant benefit of the sedative-hypnotic on insomnia measures, results on depressive symptoms were mixed. One study demonstrated that the coadministration of eszopiclone and fluoxetine resulted in improvement of depressive symptoms, even beyond the impact of sleep-related changes (20). However, similar benefits from sedative-hypnotics were not observed in a study of coadministered extended-release zolpidem and escitalopram (21).
Studies that clarify the effect of sedative-hypnotic coadministration in patients with a major depressive episode are particularly relevant in patients at risk for suicide. Insomnia is independently associated with increased suicidal behaviors and ideation (22). However, suicidal ideation has also been associated with sedative-hypnotics (23), and many psychiatrists fear that prescription of sleep medications may increase the risk of overdose. To advance this area of inquiry, the Reducing Suicidal Ideation Through Insomnia Treatment (REST-IT) study applied a similar coadministration paradigm of extended-release zolpidem versus placebo with open-label SSRI in patients with major depression, insomnia, and co-occurring suicidal ideation (24). This landmark study demonstrated that coprescription of a sedative-hypnotic and an SSRI does not worsen suicidal ideation, and in fact may reduce suicidal ideation, particularly in patients with more severe insomnia (24).
The direct effects of cognitive-behavioral therapy for insomnia (CBT-I), a highly effective nonpharmacological treatment for insomnia that is generally considered a first-line therapeutic strategy (25, 26), have not been thoroughly evaluated in depressed patients with suicidal ideation. A previous study that evaluated the effects of CBT-I on veterans with insomnia demonstrated that CBT-I may improve depressive symptoms and suicidal ideation, and that the observed relationship between insomnia severity and change in suicidal ideation remained significant even when adjusted for changes in depression severity (27). A smaller pilot trial of brief CBT-I in depressed veterans with and without suicidal ideation suggested that this modality may improve sleep, but effects on depression and suicidal ideation required larger follow-up studies (28). A subsequent larger randomized controlled trial in patients with major depression and/or posttraumatic stress disorder reporting suicidal ideation demonstrated large effects of brief CBT-I on depression and insomnia, with relatively small effects of the therapy on suicidal ideation, which were moderated by insomnia, although this effect fell short of statistical significance (29).
Beyond patients with suicidal ideation, the effects of concomitant thymoleptics and CBT-I in persons with depression and comorbid insomnia have also yielded mixed results. Initial randomized controlled pilot studies examining the use of CBT-I with coadministration of escitalopram in patients with depression and insomnia improved both insomnia symptoms and rates of depression remission compared with escitalopram and active control therapy (30). However, the larger follow-up Treatment of Insomnia in Depression (TRIAD) study, which employed a similar research paradigm, did not replicate the preliminary findings (31). Post hoc analyses suggested that childhood onset of depression and insomnia, as well as evening circadian preference, were potential moderators of depression outcomes in TRIAD (32, 33). Change in depression symptoms also were not significantly different across treatment arms in a randomized controlled trial in depression and comorbid insomnia that compared three treatment conditions: escitalopram plus CBT-I, CBT-I plus placebo, and escitalopram plus sleep hygiene control (34).
Thus, taken in aggregate, studies that have examined the effects of concomitant use of insomnia treatments (i.e., medications or CBT-I) and antidepressants in persons with depression and insomnia have reliably demonstrated improvement in insomnia measures resulting from sleep-targeted therapy. However, improvement in depressive symptoms in these study paradigms has not been as consistent. While differences among study findings may be related to granular dissimilarities between investigations, from a pragmatic standpoint, specifically addressing insomnia complaints in the context of depression is likely to have a positive therapeutic effect, at least in some instances, and may improve sequelae of depression (e.g., suicidal ideation). However, from a public health perspective, it is possible that a more critical and fruitful time to target insomnia in the treatment of depression may be prior to the onset of a depressive episode.

Can Treatment of Insomnia Prevent Depression?

The ability to effectively prevent the onset of mental illness is the holy grail of psychiatry. Unlike the majority of fields of medicine, which have successfully developed and championed preventive strategies for a variety of chronic conditions, psychiatry still largely relies on diagnosis and management after symptoms are well established. Given the large societal and economic costs of mood disorders (35), the development of effective strategies to prevent the onset of depressive episodes should be a high priority for the field. The robust longitudinal connections between insomnia and risk of subsequent depression (4, 25, 26), as well as effective pharmacological and nonpharmacological methods to treat insomnia, place insomnia as a key target for depression prevention. While the possibility that insomnia may represent a unique opportunity for prevention of mental illness has been proposed for several decades (36), the development of Internet-based CBT-I therapies that are both effective and can be widely disseminated has begun to advance this critical area of inquiry.
Large-scale studies of digital CBT-I (dCBT-I) in persons with insomnia have generally demonstrated improvements in both insomnia and depressive symptoms. The GoodNight Study was a randomized controlled trial that examined the use of dCBT-I in adults with insomnia and subthreshold depression symptoms (37). The study demonstrated that dCBT-I significantly reduced depressive symptoms but did not significantly reduce the number of participants with major depressive disorder at 6 months. Freeman et al. (38) examined the effects of dCBT-I in a large study of university students with insomnia and demonstrated large reductions in depression scores at 10- and 22-week follow-ups in dCBT-I compared with usual care, with significant reductions in the number of persons developing a major depressive episode. Large-scale randomized controlled trials of the effects of dCBT-I have replicated findings of reductions in depressive rating scales resulting from the therapy (39, 40).
More recently, Cheng et al. (41) conducted a randomized controlled trial of dCBT-I in a large group of persons with insomnia disorder, approximately half of whom had depressive symptoms rated as moderate or worse at baseline. dCBT-I was associated with significantly increased rates of depression remission at 1-year follow-up compared with the control condition (treatment as usual plus online sleep education). Baseline severity of insomnia, lack of insomnia response or remission to dCBT-I, and decreased durability of insomnia improvement with dCBT-I were conversely all associated with increased moderate to severe depression at 1-year follow-up. Notably, among individuals with minimal or no depression at baseline, the risk of developing moderate to severe depression was reduced by half in the dCBT-I relative to the control condition. When considering participants without depression at baseline, the number needed to treat to prevent depression at 1 year was 11 (41). Because of the high prevalence of insomnia in the general population (42), this finding suggests that treatment of insomnia with dCBT-I has the potential to dramatically decrease the incidence of depression if broadly available and applied. Clearly, such promising results demonstrate the need for further large-scale longitudinal research trials that focus on the ability to prevent major depressive episodes through the treatment of insomnia as a modifiable risk factor.

The Role of Sleep in Treatment-Resistant Depression

While the definition of treatment-resistant depression may vary across the literature and is not without some controversy, generally it is operationally defined as depression that fails to respond to at least two adequate therapeutic trials of an antidepressant medication (43, 44). Treatment-resistant depression has been estimated to occur in up to half of cases of major depressive disorder (43). It is a significant cause of morbidity and mortality, and its optimal treatment relies on careful history taking and a tailored approach to treatment that balances comorbidities with the risks and benefits of available treatment options. Sleep disorders, particularly obstructive sleep apnea, may play an underappreciated role in treatment-resistant depression. The overarching pathophysiology of obstructive sleep apnea consists of cycles of apneas and hypopneas—intermittent upper airway obstruction due to pharyngeal collapse during sleep, resultant drops in blood oxygenation, and arousals from sleep to temporarily resolve upper airway obstruction. Obstructive sleep apnea is associated with several negative health outcomes, including hypertension, cardiovascular disease, arrhythmia, stroke, impaired glucose regulation, cognitive impairment, and mortality (45).
The prevalence of obstructive sleep apnea among patients with major depression is higher than in the general population, with approximately 20% of persons with major depression having obstructive sleep apnea and vice versa (46). Recent data suggest that such elevated rates of obstructive sleep apnea occur in persons with major depression even in the absence of symptoms suggestive of sleep-disordered breathing (47). In addition, persons with major depression and comorbid obstructive sleep apnea may have higher rates of suicidal ideation and acts compared with those without sleep apnea (48, 49). Obstructive sleep apnea has been associated with nonresponse to antidepressant pharmacotherapy in adolescents and adults (50, 51). Randomized controlled trials have also demonstrated that positive airway pressure therapy decreases both symptoms and cases of depression in persons with obstructive sleep apnea (52). Thus, as supported by the APA practice guidelines, “Clinicians should be alert to the possibility of sleep apnea in patients with depression, particularly those who present with daytime sleepiness, fatigue, or treatment-resistant symptoms” (53).
Unfortunately, screening for sleep-disordered breathing as a contributing factor for both depression and treatment resistance is limited among practicing psychiatrists. This is likely due to several factors, including limited education about sleep disorders among mental health providers while in training (54), absence of simple blood-based laboratory testing to evaluate for the presence or absence of obstructive sleep apnea, and the high cost associated with in-laboratory polysomnography, which has long been the gold standard for the diagnosis of sleep-disordered breathing. However, with the advent of widely accessible and lower-cost methods to assess for obstructive sleep apnea in the home environment (55), barriers to sleep testing are substantially lower than in previous decades. In the case of depression, unique opportunities exist to develop models of care that more deliberately consider sleep-disordered breathing in the diagnostic and therapeutic algorithms of care provision in ambulatory and inpatient treatment settings. While the identification of obstructive sleep apnea will not likely cure depression in most patients, identifying and treating this key comorbidity may improve the efficacy of existing treatments and decrease the likelihood of treatment resistance. Clearly, further research that clarifies the impact of unidentified sleep-disordered breathing on the presentation and treatment of treatment-resistant depression is warranted.
In addition to the role of occult sleep disorders such as sleep apnea contributing to treatment resistance, data suggest that sleep itself may be related to rapid antidepressant effects of emerging therapies. Sleep deprivation has long been known to rapidly improve depressive symptoms, but its effects are generally short-lived, with return of depression after a subsequent bout of sleep (56). While sleep deprivation is thus unlikely to be a clinically useful treatment strategy for patients, it does afford the opportunity to compare its effects with other rapidly acting antidepressants to understand potential underlying mechanisms of action.
The synaptic homeostasis hypothesis posits that extended wakefulness increases net synaptic strength, with subsequent renormalization during sleep reflected by increases in sleep slow-wave activity (57). Recently, this hypothesis has been combined with the synaptic plasticity hypothesis of major depression (58, 59), positing that the enhanced homeostatic plasticity of extended wakefulness during sleep deprivation allows persons with major depression to temporarily move into a window of long-term potentiation inducibility/associative plasticity, which under normal circumstances would be unattainable in depression (60). Notably, increases in slow-wave activity and slope during non-REM sleep are observed after a single infusion of ketamine (61). Thus, hypothetically, these findings during sleep suggest that ketamine may acutely increase synaptic strength in persons with depression, which could contribute to its antidepressant properties.
However, just as the potential mechanisms underlying ketamine’s rapid antidepressant activity may be many, the effects of ketamine on sleep may extend beyond changes in sleep slow waves and include changes in sleep efficiency, continuity, and REM sleep (62). Notably, decreased nighttime wakefulness and other aspects of improved sleep have been associated with reductions in suicidal ideation resulting from ketamine treatment (63, 64). Additionally, the effects of ketamine have been hypothesized also to have an impact on circadian rhythms, which along with sleep homeostatic processes, govern the overt sleep-wake rhythm (65, 66). Further research that clarifies the connections between sleep, circadian rhythms, and rapid responses to ketamine may both elucidate underlying mechanisms of action and lead to new areas of inquiry that leverage alterations in sleep and chronobiology to optimize the antidepressant response for patients with treatment-resistant depression.

Embracing Heterogeneity to Unlock Connections Between Sleep and Depression

The fact that depression is a heterogeneous construct is evidenced by the myriad combinations of symptoms allowable under current diagnostic criteria (67). The challenge of understanding the underlying biology of depression under such circumstances has been highlighted by the National Institute of Mental Health’s Research Domain Criteria initiative (RDoC), which emphasizes the study of measurable traits that occur across psychiatric disorders rather than nosological distinctions that may have limited validity (68, 69). Just as depression is heterogeneous, so too is sleep, and too often the consideration of sleep complaints in major depression in both clinical and research contexts occurs at a superficial level. Sleep disturbances are not all the same, and reliance on brief self-report measures alone is unlikely to meaningfully advance research or clinical care at the interface between sleep and depression. Within the RDoC framework, sleep falls under “Arousal and Regulatory Systems,” with three separate constructs (arousal, circadian rhythms, and sleep-wakefulness) available to more fully characterize sleep disturbances. The need for such an expansive tool kit to study sleep highlights the fact that sleep is a complex behavior generated by the brain and affects the entire organism and its functioning during wakefulness. During our lifespan, sleep plays a key role in development, and we spend more time sleeping than any other behavior during the course of our lives. In this context, it is crucial to more carefully phenotype the nature of a given sleep complaint in depressive illness to advance scientific progress at their nexus (70).
While the preponderance of research on the connections between sleep and depression have focused on insomnia, the relationships between hypersomnolence and depression highlight the importance of multiple levels of investigation and objective phenotyping of specific sleep complaints in clarifying relationships between sleep and psychiatric disorders. Hypersomnolence, broadly defined as excessive daytime sleepiness and/or excessive sleep duration, occurs in a minority of patients with major depression but, like insomnia, is associated with treatment resistance, symptomatic relapse, increased risk of suicide, and functional impairment (71, 72). Like insomnia, hypersomnolence is also associated with longitudinal risk of developing depression (73). From a physiological standpoint, the presence or absence of hypersomnolence in major depression also has key effects on differences in regional slow-wave activity during sleep when quantified using high-density EEG (74). Like all sleep complaints, hypersomnolence has multiple facets and quantifiable aspects that must be considered to fully understand their relationships with mood disorders. In fact, these different measurable aspects of hypersomnolence are particularly critical to consider in the context of depression because different objective tests used to quantify somnolence and daytime vigilance can exhibit divergent relationships with depressive symptoms (75, 76). These more discrete measurable aspects of hypersomnolence have also proven to be critical to identifying epigenetic changes associated with sleep disturbances, which would otherwise be missed by nonspecific self-report measures (77). Thus, more thorough consideration and delineation of the sleep phenotype is just as important to understanding the connections between sleep and depression as careful consideration of the multiple symptom domains that constitute depressive illness. From a broader transdiagnostic perspective, these discrete and measurable sleep-related traits may be particularly relevant for furthering scientific inquiry across the full spectrum of psychiatric disorders.
The ability to more accurately and objectively capture key sleep measures and phenotypes has long been hindered by low accessibility and high cost. Even beyond the use of home sleep testing for obstructive sleep apnea, emerging technologies offer the opportunity to dramatically lower barriers to the objective measurement of sleep in the ambulatory environment. Such methods have great promise to be adapted to tailor personalized sleep-related therapies early in the course of treatment and potentially reduce the burden of psychiatric illness. However, consumer-grade wearables are not yet accurate enough to define sleep stages, particularly REM sleep that may occur earlier than typical, as is often observed in depression (7881). The development, production, and release of wearable products into the marketplace far outpaces their validation in persons with mood disorders, as these devices are generally designed to estimate sleep in healthy populations. In the coming years, advances in these technologies will likely lead to tools that can be leveraged at the interface of sleep and depression, but it will be critical to fully validate these products in patients with depression before they can be applied broadly in research or clinical care settings.

Conclusions

Sleep and depression are deeply intertwined on numerous levels. Careful consideration, evaluation, and treatment of sleep disturbances will inform research and clinical care in depressive disorders. Recent advances and scalability in the evaluation and treatment of sleep disorders has great promise for future advances in this area. The close longitudinal relationship between insomnia and depression offers the tantalizing opportunity to prevent depressive episodes using evidence-based treatments for insomnia, which would represent a paradigm shift for psychiatry. Recognition and clarification of the role of disordered sleep in treatment-resistant depression may improve the efficacy and effectiveness of rapid-acting antidepressants and lead to other novel therapeutics. Careful consideration and measurement of the type and nature of sleep disturbance will also lead to transdiagnostic discoveries that can be applied and studied across the full spectrum of psychiatric disorders to continue to advance our understanding of the biological bases of complex psychopathologies and their connections with sleep.

References

1.
Riemann D, Krone LB, Wulff K, et al : Sleep, insomnia, and depression. Neuropsychopharmacology 2020 ; 45 : 74 – 89
2.
Krystal AD : Psychiatric disorders and sleep. Neurol Clin 2012 ; 30 : 1389 – 1413
3.
Stewart R, Besset A, Bebbington P, et al : Insomnia comorbidity and impact and hypnotic use by age group in a national survey population aged 16 to 74 years. Sleep 2006 ; 29 : 1391 – 1397
4.
Baglioni C, Battagliese G, Feige B, et al : Insomnia as a predictor of depression: a meta-analytic evaluation of longitudinal epidemiological studies. J Affect Disord 2011 ; 135 : 10 – 19
5.
Lohoff FW : Overview of the genetics of major depressive disorder. Curr Psychiatry Rep 2010 ; 12 : 539 – 546
6.
Lind MJ, Hawn SE, Sheerin CM, et al : An examination of the etiologic overlap between the genetic and environmental influences on insomnia and common psychopathology. Depress Anxiety 2017 ; 34 : 453 – 462
7.
Hammerschlag AR, Stringer S, de Leeuw CA, et al : Genome-wide association analysis of insomnia complaints identifies risk genes and genetic overlap with psychiatric and metabolic traits. Nat Genet 2017 ; 49 : 1584 – 1592
8.
Buch AM, Liston C : Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics. Neuropsychopharmacology 2021 ; 46 : 156 – 175
9.
Bagherzadeh-Azbari S, Khazaie H, Zarei M, et al : Neuroimaging insights into the link between depression and insomnia: a systematic review. J Affect Disord 2019 ; 258 : 133 – 143
10.
Leerssen J, Blanken TF, Pozzi E, et al : Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder: results from the ENIGMA MDD Working Group. Transl Psychiatry 2020 ; 10 : 425
11.
Buysse DJ, Reynolds CF 3rd, Monk TH, et al : The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989 ; 28 : 193 – 213
12.
Cheng W, Rolls ET, Ruan H, et al : Functional connectivities in the brain that mediate the association between depressive problems and sleep quality. JAMA Psychiatry 2018 ; 75 : 1052 – 1061
13.
Drysdale AT, Grosenick L, Downar J, et al : Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med 2017 ; 23 : 28 – 38
14.
Zhao W, Van Someren EJW, Li C, et al : EEG spectral analysis in insomnia disorder: a systematic review and meta-analysis. Sleep Med Rev 2021 ; 59 : 101457
15.
Perlis ML, Smith MT, Andrews PJ, et al : Beta/gamma EEG activity in patients with primary and secondary insomnia and good sleeper controls. Sleep 2001 ; 24 : 110 – 117
16.
Kang SG, Mariani S, Marvin SA, et al : Sleep EEG spectral power is correlated with subjective-objective discrepancy of sleep onset latency in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2018 ; 85 : 122 – 127
17.
Riedner BA, Goldstein MR, Plante DT, et al : Regional patterns of elevated alpha and high-frequency electroencephalographic activity during nonrapid eye movement sleep in chronic insomnia: a pilot study. Sleep 2016 ; 39 : 801 – 812
18.
Ferrarelli F, Huber R, Peterson MJ, et al : Reduced sleep spindle activity in schizophrenia patients. Am J Psychiatry 2007 ; 164 : 483 – 492
19.
Ferrarelli F, Peterson MJ, Sarasso S, et al : Thalamic dysfunction in schizophrenia suggested by whole-night deficits in slow and fast spindles. Am J Psychiatry 2010 ; 167 : 1339 – 1348
20.
Fava M, McCall WV, Krystal A, et al : Eszopiclone co-administered with fluoxetine in patients with insomnia coexisting with major depressive disorder. Biol Psychiatry 2006 ; 59 : 1052 – 1060
21.
Fava M, Asnis GM, Shrivastava RK, et al : Improved insomnia symptoms and sleep-related next-day functioning in patients with comorbid major depressive disorder and insomnia following concomitant zolpidem extended-release 12.5 mg and escitalopram treatment: a randomized controlled trial. J Clin Psychiatry 2011 ; 72 : 914 – 928
22.
Pigeon WR, Pinquart M, Conner K : Meta-analysis of sleep disturbance and suicidal thoughts and behaviors. J Clin Psychiatry 2012 ; 73 : e1160 – e1167
23.
Tubbs AS, Fernandez FX, Ghani SB, et al : Prescription medications for insomnia are associated with suicidal thoughts and behaviors in two nationally representative samples. J Clin Sleep Med 2021 ; 17 : 1025 – 1030
24.
McCall WV, Benca RM, Rosenquist PB, et al : Reducing Suicidal Ideation Through Insomnia Treatment (REST-IT): a randomized clinical trial. Am J Psychiatry 2019 ; 176 : 957 – 965
25.
Buysse DJ : Insomnia. JAMA 2013 ; 309 : 706 – 716
26.
Winkelman JW : Clinical practice: insomnia disorder. N Engl J Med 2015 ; 373 : 1437 – 1444
27.
Trockel M, Karlin BE, Taylor CB, et al : Effects of cognitive behavioral therapy for insomnia on suicidal ideation in veterans. Sleep 2015 ; 38 : 259 – 265
28.
Pigeon WR, Funderburk J, Bishop TM, et al : Brief cognitive behavioral therapy for insomnia delivered to depressed veterans receiving primary care services: a pilot study. J Affect Disord 2017 ; 217 : 105 – 111
29.
Pigeon WR, Funderburk JS, Cross W, et al : Brief CBT for insomnia delivered in primary care to patients endorsing suicidal ideation: a proof-of-concept randomized clinical trial. Transl Behav Med 2019 ; 9 : 1169 – 1177
30.
Manber R, Edinger JD, Gress JL, et al : Cognitive behavioral therapy for insomnia enhances depression outcome in patients with comorbid major depressive disorder and insomnia. Sleep 2008 ; 31 : 489 – 495
31.
Manber R, Buysse DJ, Edinger J, et al : Efficacy of cognitive-behavioral therapy for insomnia combined with antidepressant pharmacotherapy in patients with comorbid depression and insomnia: a randomized controlled trial. J Clin Psychiatry 2016 ; 77 : e1316 – e1323
32.
Asarnow LD, Bei B, Krystal A, et al : Circadian preference as a moderator of depression outcome following cognitive behavioral therapy for insomnia plus antidepressant medications: a report from the TRIAD study. J Clin Sleep Med 2019 ; 15 : 573 – 580
33.
Edinger JD, Manber R, Buysse DJ, et al : Are patients with childhood onset of insomnia and depression more difficult to treat than are those with adult onsets of these disorders? A report from the TRIAD study. J Clin Sleep Med 2017 ; 13 : 205 – 213
34.
Carney CE, Edinger JD, Kuchibhatla M, et al : Cognitive behavioral insomnia therapy for those with insomnia and depression: a randomized controlled clinical trial. Sleep 2017 ; 40 : zsx019
35.
GBD 2019 Diseases and Injuries Collaborators : Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020 ; 396 : 1204 – 1222
36.
Ford DE, Kamerow DB : Epidemiologic study of sleep disturbances and psychiatric disorders: an opportunity for prevention? JAMA 1989 ; 262 : 1479 – 1484
37.
Christensen H, Batterham PJ, Gosling JA, et al : Effectiveness of an online insomnia program (SHUTi) for prevention of depressive episodes (the GoodNight Study): a randomised controlled trial. Lancet Psychiatry 2016 ; 3 : 333 – 341
38.
Freeman D, Sheaves B, Goodwin GM, et al : The effects of improving sleep on mental health (OASIS): a randomised controlled trial with mediation analysis. Lancet Psychiatry 2017 ; 4 : 749 – 758
39.
Espie CA, Emsley R, Kyle SD, et al : Effect of digital cognitive behavioral therapy for insomnia on health, psychological well-being, and sleep-related quality of life: a randomized clinical trial. JAMA Psychiatry 2019 ; 76 : 21 – 30
40.
Vedaa Ø, Kallestad H, Scott J, et al : Effects of digital cognitive behavioural therapy for insomnia on insomnia severity: a large-scale randomised controlled trial. Lancet Digit Health 2020 ; 2 : e397 – e406
41.
Cheng P, Kalmbach DA, Tallent G, et al : Depression prevention via digital cognitive behavioral therapy for insomnia: a randomized controlled trial. Sleep 2019 ; 42 : zsz150
42.
Ohayon MM : Epidemiology of insomnia: what we know and what we still need to learn. Sleep Med Rev 2002 ; 6 : 97 – 111
43.
Berlim MT, Turecki G : What is the meaning of treatment resistant/refractory major depression (TRD)? A systematic review of current randomized trials. Eur Neuropsychopharmacol 2007 ; 17 : 696 – 707
44.
Rush AJ, Thase ME, Dubé S : Research issues in the study of difficult-to-treat depression. Biol Psychiatry 2003 ; 53 : 743 – 753
45.
Veasey SC, Rosen IM : Obstructive sleep apnea in adults. N Engl J Med 2019 ; 380 : 1442 – 1449
46.
Ohayon MM : The effects of breathing-related sleep disorders on mood disturbances in the general population. J Clin Psychiatry 2003 ; 64 : 1195 – 1200
47.
McCall WV, Benca RM, Rumble ME, et al : Prevalence of obstructive sleep apnea in suicidal patients with major depressive disorder. J Psychiatr Res 2019 ; 116 : 147 – 150
48.
Reddy A, Mansuri Z, Vadukapuram R, et al : Increased suicidality and worse outcomes in MDD patients with OSA: a nationwide inpatient analysis of 11 years from 2006 to 2017. J Acad Consult Liaison Psychiatry (Online ahead of print, June 7, 2021)
49.
Bishop TM, Ashrafioun L, Pigeon WR : The association between sleep apnea and suicidal thought and behavior: an analysis of national survey data. J Clin Psychiatry 2018 ; 79 : 17m11480
50.
Waterman L, Stahl ST, Buysse DJ, et al : Self-reported obstructive sleep apnea is associated with nonresponse to antidepressant pharmacotherapy in late-life depression. Depress Anxiety 2016 ; 33 : 1107 – 1113
51.
Robillard R, Chase T, Courtney D, et al : Sleep-related breathing disturbances in adolescents with treatment resistant depression. Sleep Med 2019 ; 56 : 47 – 51
52.
Jackson ML, Tolson J, Schembri R, et al : Does continuous positive airways pressure treatment improve clinical depression in obstructive sleep apnea? A randomized wait-list controlled study. Depress Anxiety 2021 ; 38 : 498 – 507
53.
American Psychiatric Association : Practice Guideline for the Treatment of Patients With Major Depressive Disorder, 3rd ed. Washington, DC, American Psychiatric Association, 2010
54.
Krahn LE, Hansen MR, Tinsley JA : Psychiatric residents’ exposure to the field of sleep medicine: a survey of program directors. Acad Psychiatry 2002 ; 26 : 253 – 256
55.
Rosen CL, Auckley D, Benca R, et al : A multisite randomized trial of portable sleep studies and positive airway pressure autotitration versus laboratory-based polysomnography for the diagnosis and treatment of obstructive sleep apnea: the HomePAP study. Sleep 2012 ; 35 : 757 – 767
56.
Wu JC, Bunney WE : The biological basis of an antidepressant response to sleep deprivation and relapse: review and hypothesis. Am J Psychiatry 1990 ; 147 : 14 – 21
57.
Tononi G, Cirelli C : Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration. Neuron 2014 ; 81 : 12 – 34
58.
Castrén E : Is mood chemistry? Nat Rev Neurosci 2005 ; 6 : 241 – 246
59.
Kuhn M, Mainberger F, Feige B, et al : State-dependent partial occlusion of cortical LTP-like plasticity in major depression. Neuropsychopharmacology 2016 ; 41 : 2794
60.
Wolf E, Kuhn M, Normann C, et al : Synaptic plasticity model of therapeutic sleep deprivation in major depression. Sleep Med Rev 2016 ; 30 : 53 – 62
61.
Duncan WC Jr, Zarate CA Jr : Ketamine, sleep, and depression: current status and new questions. Curr Psychiatry Rep 2013 ; 15 : 394
62.
Duncan WC Jr, Ballard ED, Zarate CA : Ketamine-induced glutamatergic mechanisms of sleep and wakefulness: insights for developing novel treatments for disturbed sleep and mood. Handb Exp Pharmacol 2019 ; 253 : 337 – 358
63.
Vande Voort JL, Ballard ED, Luckenbaugh DA, et al : Antisuicidal response following ketamine infusion is associated with decreased nighttime wakefulness in major depressive disorder and bipolar disorder. J Clin Psychiatry 2017 ; 78 : 1068 – 1074
64.
Rodrigues NB, McIntyre RS, Lipsitz O, et al : Do sleep changes mediate the anti-depressive and anti-suicidal response of intravenous ketamine in treatment-resistant depression? J Sleep Res (Online ahead of print, June 16, 2021)
65.
Duncan WC Jr, Slonena E, Hejazi NS, et al : Motor-activity markers of circadian timekeeping are related to ketamine’s rapid antidepressant properties. Biol Psychiatry 2017 ; 82 : 361 – 369
66.
Kohtala S, Alitalo O, Rosenholm M, et al : Time is of the essence: coupling sleep-wake and circadian neurobiology to the antidepressant effects of ketamine. Pharmacol Ther 2021 ; 221 : 107741
67.
American Psychiatric Association : Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Washington, DC, American Psychiatric Association, 2013
68.
Insel TR : The NIMH Research Domain Criteria (RDoC) project: precision medicine for psychiatry. Am J Psychiatry 2014 ; 171 : 395 – 397
69.
Cuthbert BN, Insel TR : Toward the future of psychiatric diagnosis: the seven pillars of RDoC. BMC Med 2013 ; 11 : 126
70.
Geiser T, Hertenstein E, Fehér K, et al : Targeting arousal and sleep through noninvasive brain stimulation to improve mental health. Neuropsychobiology 2020 ; 79 : 284 – 292
71.
Kaplan KA, Harvey AG : Hypersomnia across mood disorders: a review and synthesis. Sleep Med Rev 2009 ; 13 : 275 – 285
72.
Plante DT : Hypersomnia in mood disorders: a rapidly changing landscape. Curr Sleep Med Rep 2015 ; 1 : 122 – 130
73.
Plante DT, Finn LA, Hagen EW, et al : Longitudinal associations of hypersomnolence and depression in the Wisconsin Sleep Cohort Study. J Affect Disord 2017 ; 207 : 197 – 202
74.
Plante DT, Cook JD, Barbosa LS, et al : Establishing the objective sleep phenotype in hypersomnolence disorder with and without comorbid major depression. Sleep 2019 ; 42 : zsz060
75.
Plante DT, Finn LA, Hagen EW, et al : Subjective and objective measures of hypersomnolence demonstrate divergent associations with depression among participants in the Wisconsin Sleep Cohort Study. J Clin Sleep Med 2016 ; 12 : 571 – 578
76.
Plante DT, Hagen EW, Ravelo LA, et al : Impaired neurobehavioral alertness quantified by the psychomotor vigilance task is associated with depression in the Wisconsin Sleep Cohort study. Sleep Med 2020 ; 67 : 66 – 70
77.
Plante DT, Papale LA, Madrid A, et al : PAX8/PAX8-AS1 DNA methylation levels are associated with objective sleep duration in persons with unexplained hypersomnolence using a deep phenotyping approach. Sleep (Online ahead of print, June 18, 2021)
78.
Cook JD, Eftekari SC, Dallmann E, et al : Ability of the Fitbit Alta HR to quantify and classify sleep in patients with suspected central disorders of hypersomnolence: a comparison against polysomnography. J Sleep Res 2019 ; 28 : e12789
79.
Cook JD, Prairie ML, Plante DT : Ability of the Multisensory Jawbone UP3 to quantify and classify sleep in patients with suspected central disorders of hypersomnolence: a comparison against polysomnography and actigraphy. J Clin Sleep Med 2018 ; 14 : 841 – 848
80.
Cook JD, Prairie ML, Plante DT : Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: a comparison against polysomnography and wrist-worn actigraphy. J Affect Disord 2017 ; 217 : 299 – 305
81.
Benca RM, Obermeyer WH, Thisted RA, et al : Sleep and psychiatric disorders: a meta-analysis. Arch Gen Psychiatry 1992 ; 49 : 651 – 668

Information & Authors

Information

Published In

Go to American Journal of Psychiatry
Go to American Journal of Psychiatry
American Journal of Psychiatry
Pages: 896 - 902
PubMed: 34592843

History

Accepted: 18 August 2021
Published online: 1 October 2021
Published in print: October 01, 2021

Keywords

  1. Depressive Disorders
  2. Sleep Disorders

Authors

Details

David T. Plante, M.D., Ph.D. [email protected]
Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison.

Notes

Send correspondence to Dr. Plante ([email protected]).

Competing Interests

Dr. Plante has received research support from the American Sleep Medicine Foundation, the Brain and Behavior Research Foundation, the Madison Education Partnership, the National Institute of Nursing Research, the National Institute on Aging, NIMH, and the University of Illinois at Chicago Occupational and Environmental Health and Safety Education and Research Center (funded by the National Institute for Occupational Safety and Health); he has served as a consultant and/or advisory board member for Harmony Biosciences, Jazz Pharmaceuticals, and Teva Pharmaceuticals Australia; and he has received honoraria from the American Academy of Sleep Medicine and royalties from Cambridge University Press.

Metrics & Citations

Metrics

Citations

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format
Citation style
Style
Copy to clipboard

View Options

View options

PDF/EPUB

View PDF/EPUB

Login options

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Personal login Institutional Login Open Athens login
Purchase Options

Purchase this article to access the full text.

PPV Articles - American Journal of Psychiatry

PPV Articles - American Journal of Psychiatry

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Media

Figures

Other

Tables

Share

Share

Share article link

Share