Polysomnography in seasonal affective disorder: A systematic review and meta-analysis

Multidimensional assessment of adverse events of bupropion: A large-scale data analysis from the FAERS database

OBJECTIVE

Bupropion, a monocyclic antidepressant, aids in smoking cessation, treats major depression, and prevents severe depression in seasonal affective disorder patients. Yet, its adverse reactions remain insufficiently studied.

METHODS

All data from the raw data packages for 78 quarters from the 1st quarter of 2004 to the 2nd quarter of 2023 were extracted from the FDA Adverse Event Reporting System (FAERS) database and imported into the SAS9.4 software for data cleaning and analysis. The Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS) methods were used to analyze drug adverse events and assess their compliance with various screening criteria.

RESULTS

The results showed a total of 36,862 reports related to Bupropion use, identifying 364 positive reaction terms (PT) covering 23 System Organ Classes (SOCs). In addition to known side effects, some new potential adverse reactions were found, such as Stool analysis abnormal, Oculocephalogyric reflex absent, Suspected suicide, and so on. At the same time, reactions like Encephalopathy neonatal, Hyponatraemic coma, and Electrocardiogram QRS complex prolonged were prominently ranked. Notably, occurrences such as Urine amphetamine positive and Amphetamines positive were relatively high, suggesting extra caution for these potential adverse reactions during clinical use of Bupropion.

CONCLUSION

These findings highlight the potential health risks of long-term Bupropion use, especially concerning efficacy, positive drug tests, and suicidal tendencies. Therefore, it is recommended to monitor and assess patients using Bupropion more stringently to use this therapeutically potential drug more safely and effectively.

Major depressive disorder with hypersomnolence complaint: A comparison study with non-depressed individuals examining objective biomarkers

BACKGROUND

Hypersomnolence is common in major depressive disorder (MDD), associated with more severe episodes, suicide and antidepressant resistance. Nevertheless, few studies used polysomnography (PSG) and multiple sleep latency test (MSLT) to characterize these patients. In this context, we compared patients visiting a sleep center for hypersomnolence complaint with MDD (HSC/MDD+) and without MDD (HSC/MDD-).

METHODS

HSC/MDD+ and HSC/MDD- groups were defined according to DSM-5 criteria and CES-D scale, and had a 30 h-PSG with ad libitum-sleep and PSG followed by MLST.

RESULTS

HSC/MDD+ had an increased self-declared total sleep time (sTST) of about 10 h30 similar to HSC/MDD- (630.8 ± 17.3 min-vs-616.5 ± 18.1 min, respectively, p = 0.39). Nevertheless, their objective TST (oTST) on ad libitum PSG was significantly longer and about 10 h50 (648.6 ± 23.9 min-vs-587.4 ± 19.0 min, respectively, p = 0.038). HSC/MDD+ also significantly better estimated their sleep duration, with a lower difference between their sTST and oTST compared to HSC/MDD- (10.0 ± 1.7 %-vs-17.4 ± 2.1 %, respectively, p = 0.009) and confirmed significantly more frequently the hypersomnia diagnosis -i.e. oTST>10H- (82.6 ± 8.1 %-vs-54.6 ± 10.9 %, respectively, p = 0.046). Using the Kupfer index (KI), we confirmed a reduced REM sleep latency in patients MDD/HSC+ (15.2 ± 10.0 %-vs-2.3 ± 2.3 %, respectively, p = 0.039). Both groups had comparable increased diurnal sleepiness assessed with the Epworth scale (14.1 ± 1.1-vs-14.8 ± 1.1, respectively, p = 0.65). HSC/MDD+ had less MSLT sleep latency <8 min (9.1 ± 5.1 %-vs-27.3 ± 6.8 %, respectively, p = 0.048).

LIMITATIONS

Retrospective cross-sectional study.

CONCLUSIONS

HSC/MDD+ accurately estimated their sleep duration, objectively confirmed hypersomnia and may specifically had a decreased Kupfer index.

Major depressive episode with insomnia and excessive daytime sleepiness: A more homogeneous and severe subtype of depression

Previous studies have noted the crucial role of excessive daytime sleepiness (EDS) in the course of depressive illness, and more recently, a few studies documented its strong associations with an increased risk of suicide. While insomnia is associated with heightened emotional reactivity, suicidal behaviors, and increased relapses and recurrence. Our main hypothesis is that major depressive episodes (MDE) with insomnia and EDS are associated with more severe manifestations of depression. However, to date, no study has directly compared MDE with insomnia without EDS (Ins), and MDE with insomnia with EDS (InsEDS) using both subjective biomarkers (administration of self-assessment questionnaires for psychiatric evaluation and sleep complaints) and objective biomarkers (of sleep and circadian rhythms (using actigraphy). The InsEDS group, compared to the Ins group, exhibited significantly increased suicidal ideation, larger seasonal impacts on mood, alterations in sleep duration, weight, appetite, energy levels, and social activities throughout the year. Furthermore, they had significant delayed onset of daily activity measured with actigraphy. These findings provided new insights into the link between suicide, sleep, alertness, and biological clock. They also hold significant implications for identifying individuals with more severe depressive manifestations and for developing tailored and personalized therapeutic strategies.

Vivid dreams are associated with a high percentage of REM sleep: a prospective study in veterans

STUDY OBJECTIVES

Vivid dreams are dreams that feel real or are associated with dream enactment behavior. They are prevalent in veterans, especially in those with psychiatric disorders such as post-traumatic stress disorders. Such psychiatric disorders have known association with abnormalities in rapid eye movement (REM) sleep. Vivid dreams are also described in neurological conditions, such Lewy body dementias, which are also associated with REM sleep abnormality. Although vivid dreams occur in neuropsychiatric disorders that have REM sleep abnormalities, there are no studies that have directly investigated an association between vivid dreams and REM sleep. We sought to study vivid dreams and REM sleep in veterans.

METHODS

Veterans undergoing polysomnography at our hospital were invited to enroll. Participants completed a dream-related questionnaire the morning after their polysomnography.

RESULTS

We prospectively enrolled 505 veterans. After a night in the sleep laboratory, 196 of 504 (39%) reported experiencing a dream, and, of those, 117 of 190 (62%) described their dream as vivid. Discrepancies in patient totals are secondary to missing questionnaire data. Our novel finding is that participants with a high percentage of REM sleep (above 25%) were more than twice likely to report a vivid dream than participants with a lower percentage of REM sleep (P < .0001). Nonvivid dreams were not associated with a high percentage of REM sleep.

CONCLUSIONS

Vivid dreams are associated with a high percentage of REM sleep. Further research into the role of REM sleep abnormalities in vivid dreams may help to advance understanding of neuropsychiatric disorders.

CITATION

Fattal D, Platti N, Hester S, Wendt L. Vivid dreams are associated with a high percentage of REM sleep: a prospective study in veterans. J Clin Sleep Med. 2023;19(9):1661-1668.

Patterns of polysomnography parameters in 27 neuropsychiatric diseases: an umbrella review

BACKGROUND

We provide an umbrella review of the reported polysomnographic changes in patients with neuropsychiatric diseases compared with healthy controls.

METHODS

An electronic literature search was conducted in EMBASE, MEDLINE, All EBM databases, CINAHL, and PsycINFO. Meta-analyses of case-control studies investigating the polysomnographic changes in patients with neuropsychiatric diseases were included. For each meta-analysis, we estimated the summary effect size using random effects models, the 95% confidence interval, and the 95% prediction interval. We also estimated between-study heterogeneity, evidence of excess significance bias, and evidence of small-study effects. The levels of evidence of polysomnographic changes in neuropsychiatric diseases were ranked as follows: not significant, weak, suggestive, highly suggestive, or convincing.

RESULTS

We identified 27 articles, including 465 case-control studies in 27 neuropsychiatric diseases. The levels of evidence of polysomnographic changes in neuropsychiatric diseases were highly suggestive for increased sleep latency and decreased sleep efficiency (SE) in major depressive disorder (MDD), increased N1 percentage, and decreased N2 percentage, SL and REML in narcolepsy, and decreased rapid eye movement (REM) sleep percentage in Parkinson's disease (PD). The suggestive evidence decreased REM latency in MDD, decreased total sleep time and SE in PD, and decreased SE in posttraumatic stress disorder and in narcolepsy.

CONCLUSIONS

The credibility of evidence for sleep characteristics in 27 neuropsychiatric diseases varied across polysomnographic variables and diseases. When considering the patterns of altered PSG variables, no two diseases had the same pattern of alterations, suggesting that specific sleep profiles might be important dimensions for defining distinct neuropsychiatric disorders.

Here comes the sun: music features of popular songs reflect prevailing weather conditions

We examine associations between prevailing weather conditions and music features in all available songs that reached the United Kingdom weekly top charts throughout a 67-year period (1953-2019), comprising 23 859 unique entries. We found that music features reflecting high intensity and positive emotions were positively associated with daily temperatures and negatively associated with rainfall, whereas music features reflecting low intensity and negative emotions were not related to weather conditions. These results held true after controlling for the mediating effects of year (temporal patterns) and month (seasonal patterns). However, music-weather associations were more nuanced than previously assumed by linear models, becoming only meaningful in those months and seasons when changes in weather were the most notable. Importantly, the observed associations depended on the popularity of the music: while songs in the top 10 of the charts exhibited the strongest associations with weather, less popular songs showed no relationship. This suggests that a song's fit with prevailing weather may be a factor pushing a song into the top of the charts. Our work extends previous research on non-musical domains (e.g. finance, crime, mental health) by showing that large-scale population-level preferences for cultural phenomena (music) are also influenced by broad environmental factors that exist over long periods of time (weather) via mood-regulation mechanisms. We discuss these results in terms of the limited nature of correlational studies and cross-cultural generalizability.

Predictive biosignature of major depressive disorder derived from physiological measurements of outpatients using machine learning

Major Depressive Disorder (MDD) has heterogeneous manifestations, leading to difficulties in predicting the evolution of the disease and in patient's follow-up. We aimed to develop a machine learning algorithm that identifies a biosignature to provide a clinical score of depressive symptoms using individual physiological data. We performed a prospective, multicenter clinical trial where outpatients diagnosed with MDD were enrolled and wore a passive monitoring device constantly for 6 months. A total of 101 physiological measures related to physical activity, heart rate, heart rate variability, breathing rate, and sleep were acquired. For each patient, the algorithm was trained on daily physiological features over the first 3 months as well as corresponding standardized clinical evaluations performed at baseline and months 1, 2 and 3. The ability of the algorithm to predict the patient's clinical state was tested using the data from the remaining 3 months. The algorithm was composed of 3 interconnected steps: label detrending, feature selection, and a regression predicting the detrended labels from the selected features. Across our cohort, the algorithm predicted the daily mood status with 86% accuracy, outperforming the baseline prediction using MADRS alone. These findings suggest the existence of a predictive biosignature of depressive symptoms with at least 62 physiological features involved for each patient. Predicting clinical states through an objective biosignature could lead to a new categorization of MDD phenotypes.

Validation of a data collection set for the psychiatric, addiction, sleep and chronobiological assessments of patients with depression: A Delphi study for the SoPsy-depression French national cohort

OBJECTIVES

Despite international efforts to identify biomarkers of depression, none has been transferred to clinical practice, neither for diagnosis, evolution, nor therapeutic response. This led us to build a French national cohort (through the clinical and research network named SoPsy within the French biological psychiatry society (AFPBN) and sleep society (SFRMS)), to better identify markers of sleep and biological rhythms and validate more homogeneous subgroups of patients, but also to specify the manifestations and pathogeneses of depressive disorders. Before inclusions, we sought to provide a predefined, standardized, and robust set of data to be collected in all centers.

METHODS

A Delphi process was performed to achieve consensus through the independent rating of invited experts, the SoPsy-depression co-investigators (n=34). The initial set open for vote included 94 questionnaires targeting adult and child psychiatry, sleep and addiction.

RESULTS

Two questionnaire rounds were completed with 94% participation in the first round and 100% participation in the second round. The results of the Delphi survey incorporated the consensus opinion of the 32 members who completed both rounds. Nineteen of the 94 questionnaires achieved consensus at the first round and seventy of 75 at the second round. The five remaining questionnaires were submitted to three experts involved in the steering committee during a dedicated meeting. At the end, 24 questionnaires were retained in the mandatory and 26 in the optional questionnaire set.

CONCLUSIONS

A validated data collection set of questionnaires is now available to assess psychiatry, addiction, sleep and chronobiology dimensions of depressive disorders.

Sleep and circadian rhythm profiles in seasonal depression

Sleep and circadian rhythm disruptions are symptoms of, and hypothesized underlying mechanisms in, seasonal depression. Discrepant observational findings and mixed responses to sleep/circadian-based treatments suggest heterogenous sleep and circadian disruptions in seasonal depression, despite these disruptions historically conceptualized as delayed circadian phase and hypersomnia. This study used a data-driven cluster analysis to characterize sleep/circadian profiles in seasonal depression to identify treatment targets for future interventions. Biobehavioral measures of sleep and circadian rhythms were assessed during the winter in individuals with Seasonal Affective Disorder (SAD), subsyndromal-SAD (S-SAD), or nonseasonal, never depressed controls (total sample N = 103). The following variables were used in the cluster analysis: circadian phase (from dim light melatonin onset), midsleep timing, total sleep time, sleep efficiency, regularity of midsleep timing, and nap duration (all from wrist actigraphy). Sleep and circadian variables were compared across clusters and controls. Despite limited sleep/circadian differences between diagnostic groups, there were two reliable (Jaccard Coefficients >0.75) sleep/circadian profiles in SAD/S-SAD individuals: a 'Disrupted sleep' cluster, characterized by irregular and fragmented sleep and an 'Advanced' cluster, characterized by early sleep and circadian timing and longer total sleep times (>7.5 h). Clusters did not differ by depression severity. Midsleep correlated with DLMO (r = 0.56), irregularity (r = 0.3), and total sleep time (r = -0.27). Sleep and circadian disruptions in seasonal depression are not uniformly characterized by hypersomnia and circadian phase delay. Presence of distinct sleep and circadian subgroups in seasonal depression may predict successful treatment response. Prospective assessment and tailoring of individual sleep and circadian disruptions may reduce treatment failures.

Melatonergic agents influence the sleep-wake and circadian rhythms in healthy and psychiatric participants: a systematic review and meta-analysis of randomized controlled trials

Exogenous melatonergic agents are widely used to treat insomnia and sleep disturbance. Several studies have shown that they might also modulate circadian rhythms. The purpose of this systematic review and meta-analysis was to summarize current knowledge about the effects of melatonin supplements and melatonin agonists on the sleep-wake cycle as well as on the circadian rhythm of melatonin in healthy participants and in patients with psychiatric disorders. The following electronic databases were searched: EMBASE, PubMed, Web of Science, CINAHL, and Cochrane Library. Of the 12,719 articles, we finally selected 30 studies including 1294 healthy participants and 8 studies including 687 patients with psychiatric disorders. Cochrane risk of bias tool was used to assess the risk of bias. Using meta-ANOVA, studies on healthy participants showed advancing effects of melatonergic supplements and agonists on sleep-wake cycle according to dosing time and dosage, despite the fact that the original individual melatonin rhythm was within a normal range (fixed effect model standardized mean difference [95% Confidence Interval] = -0.639[-0.968 to -0.310]). In a limited number of randomized controlled trials with psychiatric patients, the findings seemed similar to those with healthy participants, despite the psychiatric disorders and treatment related factors affecting circadian rhythms. Given the unmet clinical need for evidence-based treatments to correct circadian rhythms in psychiatric disorders, efficacy of melatonergic agents seen in healthy participants, and similarity of findings among psychiatric patients, large scale, well-designed randomized controlled trials are needed to test efficacy on circadian parameters in psychiatric disorders.

Role of Melatonin in the Management of Sleep and Circadian Disorders in the Context of Psychiatric Illness

PURPOSE OF REVIEW

We present a review of research on the role of melatonin in the management of sleep and circadian disorders, stressing current overall view of the knowledge across psychiatric disorders.

RECENT FINDINGS

Dysregulation of sleep and circadian rhythms has been established in several psychiatric and neurocognitive disorders for long. Recent research confirms this finding consistently across disorders. The secretion of melatonin in schizophrenia and neurocognitive disorders is reduced due to a smaller volume and enlarged calcification of the pineal gland. On the other hand, melatonin dysregulation in bipolar disorder may be more dynamic and caused by light-sensitive melatonin suppression and delayed melatonin secretion. In both cases, exogenous melatonin seems indicated to correct the dysfunction. However, a very limited number of well-designed trials with melatonin to correct sleep and circadian rhythms exist in psychiatric disorders, and the evidence for efficacy is robust only in autism, attention deficit hyperactivity disorder (ADHD), and neurocognitive disorders. This topic has mainly not been of interest for recent work and well-designed trials with objective circadian parameters are few. Overall, recent studies in psychiatric disorders reported that melatonin can be effective in improving sleep parameters such as sleep onset latency, sleep efficiency, and sleep quality. Recent meta-analysis suggests that optimal dosage and dosing time might be important to maximize the efficacy of melatonin. The knowledge base is sufficient to propose well-designed, larger trials with circadian parameters as inclusion and outcome criteria. Based on the partly fragmentary information, we propose testing efficacy in disorders with neurocognitive etiopathology with later and higher dosing, and affective and anxiety disorders with lower and earlier dosing of melatonin. Melatonin is promising for the correction of sleep and circadian abnormalities in psychiatric disorders. However, research results on its effect are still few and need to be accumulated. For effective use of melatonin, it is necessary to consider the appropriate dosage and administration time, depending on the individual abnormality of sleep and circadian rhythms.