Genetically Proxied Diurnal Preference, Sleep Timing, and Risk of Major Depressive Disorder

Mendelian randomization of individual sleep traits associated with major depressive disorder

BACKGROUND

Observational studies have shown that individual sleep traits habits are potential risk factors for major depression. However, it is not known whether there is a causal relationship between individual sleep traits habits such as continuous sleep duration, short sleep duration, short sleep duration, insomnia, nap during the day, snoring, and major depression. In this study, Mendelian randomization (MR) was used to predict major depressive disorder (MDD) in individuals sleep traits habits.

METHODS

Data were obtained from the genome-wide association study (GWAS). Nine MR analysis methods were used: Inverse Variance Weighted (IVW) [fixed effects/multiplicative random effects], simple mode, simple mode, weighted mode, simple median, weighted median, penalised weighted median, and MR-Egger, MR Egger (bootstrap). IVW was used as the main analysis method for the MR analysis of two samples, and the other methods were used as supplements.

RESULTS

The results obtained through the IVW method supported a causal relationship between sleep duration and decreased risk of MDD (odds ratio, ORivw: 0.998; 95 % CI: 0.996-0.999, P<0.001). Two-Sample MR, results showed that short sleep duration has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.179; 95 % CI: 1.108-1.255, P<0.001). However, there were no sufficient evidence supported that long sleep duration has a causal effect on the decreased risk of MDD (odds ratio, ORivw: 0.991; 95 % CI: 0.924-1.062, P = 0.793). A significant causal relationship between insomnia and increased risk of MDD was observed (OR: 1.233; 95 % CI: 1.214-1.253, P<0.001). Interestingly, our study also found that daytime napping has a causal effect on the increased risk of MDD (odds ratio, ORivw: 1.519; 95 % CI: 1.376-1.678, P<0.001). The present results did not show a significant causal relationship between snoring and the risk of MDD (ORivw: 1.000; 95 % CI: 0.998-1.002, P = 0.906). Obstructive sleep apnea (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) and morning person (odds ratio, ORivw: 1.021; 95 % CI: 0.972-1.072, P = 0.407) have no causal effect on the increased risk of MDD.

LIMITATIONS

The study could not ascertain whether there were genetic differences among different ethnicities, nations, and regions, as it only included participants of European ancestry.

CONCLUSIONS

In summary, our research provides genetic evidence for the relationship between individual sleep traits (short sleep duration, insomnia, daytime napping) and the increased risk of MDD. Interventions targeting lifestyle factors may reduce the risk of MDD.

The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder

BACKGROUND

Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity.

METHODS

Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393).

RESULTS

Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %.

LIMITATIONS

Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected.

CONCLUSION

Our study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions.

Sleep inertia drives the association of evening chronotype with psychiatric disorders: epidemiological and genetic evidence

Evening chronotypes (a.k.a. "night-owls") are held to be at greater risk for psychiatric disorders. This is postulated to be due to delayed circadian timing increasing the likelihood of circadian misalignment in an early-oriented society. Circadian misalignment is known to heighten sleep inertia, the difficulty transitioning from sleep to wake characterized by low arousal and cognitive impairment, and evening chronotypes experience greater sleep inertia. Therefore, difficulty awakening may explain the relationship between evening chronotype and psychiatric disorders by acting as a biomarker of circadian misalignment. In analyzing the longitudinal incidence of psychiatric disorders in the UK Biobank (n = 496,820), we found that evening chronotype predicted increased incidence of major depressive disorder, schizophrenia, generalized anxiety disorder and bipolar disorder. Crucially, this effect was dependent on sleep inertia, which was a much stronger predictor of these disorders, such that evening types without sleep inertia were at no higher risk as compared to morning types. Longitudinal analyses of suicide and depressed mood (CES-D score) in the Older Finnish Twin Cohort (n = 23,854) replicated this pattern of results. Twin and genome-wide association analyses of difficulty awakening identified the trait to be heritable (Twin H 2 = 0.40; SNP h 2 = 0.08), enriched for circadian rhythms genes and have substantial shared genetic architecture with chronotype. Marginal and conditional Mendelian randomization analyses mirrored the epidemiological results, such that the causal effect of evening chronotype on psychiatric disorders was driven by shared genetic architecture with difficulty awakening. In contrast, difficult awakening was strongly causally associated with psychiatric disorders independently of chronotype. Psychiatric disorders were only weakly reverse causally linked to difficult awakening. Collectively, these results challenge the notion that evening chronotype is a risk factor for psychiatric disorders per se, suggesting instead that evening types are at greater risk for psychiatric disorders due to circadian misalignment, for which sleep inertia may be acting as a biomarker.

Home parenteral nutrition, sleep patterns, and depressive symptoms: Secondary analysis of cross-sectional data

BACKGROUND

Patients receiving home parenteral nutrition (HPN) are known to experience psychological distress and have profoundly disrupted sleep. The aim of this analysis was to examine the relationship between sleep patterns with depressive symptoms and HPN characteristics.

METHODS

The study was a secondary analysis of cross-sectional data examining sleep patterns using subjective and objective measures. Sleep was assessed by surveys and 7-day actigraphy. The Patient Health Questionnaire-8 was used to evaluate depressive symptoms. Participants provided information on HPN. Spearman correlations were calculated between sleep measures with depressive symptoms and HPN characteristics. Correlations were further examined in multivariable linear regression models.

RESULTS

Thirty-two adults (age = 53 years; 75% female; 94% White) were included. Lower sleep quality (r = 0.54-0.60; P < 0.001) and later sleep timing (r = -0.35; P = 0.049) were correlated with higher depressive symptoms. Sleep patterns were also correlated with several HPN characteristics (r = -0.47 to 0.51). In linear regression models, rate of infusion was associated with sleep duration (β = -0.004 [0.002] h; P = 0.046) in which each 100 mL/h was associated with 24-min shorter duration. Higher total energy was associated with lower sleep quality (β = 0.0004 [0.0002] log-unit; P = 0.042), and higher volume was associated with longer sleep onset latency (β = 0.0006 [0.0003] log-min; P = 0.049).

CONCLUSIONS

We provide evidence supporting the link between poor and later sleep with higher depressive symptoms and identify potentially modifiable infusion characteristics (notably, slower rate of infusion and lower total energy and volume) that, on further verification, may support sleep among those receiving HPN.

Sleep-wake changes and incident depressive symptoms in midlife women

Our study aimed to investigate the relationship between sleep-wake changes and depressive symptoms events among midlife women. We enrolled 1579 women aged 44-56 years who had no clinically relevant depressive symptoms at baseline. Depressive symptoms were assessed at each visit using the Center for Epidemiologic Studies Depression scale. At the third and fourth follow-up visits, women reported their sleep habits. The sleep midpoint was defined as the time to fall asleep plus one-half of the sleep duration. Sleep-wake changes were determined by the difference in the midpoint of sleep between the third and fourth visits, which were 1 year apart. The median follow-up time was 7 years (range 1-7 years). Cox proportional hazard models were fitted to calculate hazard ratios and 95% confidence intervals for the incidence of depressive symptoms associated with sleep-wake changes. After adjusting for potential confounding factors, the hazard ratio (95% confidence interval) of depressive symptoms for severe sleep midpoint changes was 1.51 (1.12, 2.05) compared with mild sleep midpoint changes. This relationship remained statistically significant and changed little when additionally controlling for sleep duration, sleep quality, insomnia symptoms, use of sleep medications, use of nervous medications, glucose, insulin, lipids, dietary energy intake, and C-reactive protein. Our findings indicate that exposure to long-term severe sleep-wake changes increases the risk of depressive symptoms in midlife women.

Dissecting the genetic and causal relationship between sleep-related traits and common brain disorders

BACKGROUND

There is a profound connection between abnormal sleep patterns and brain disorders, suggesting a shared influential association. However, the shared genetic basis and potential causal relationships between sleep-related traits and brain disorders are yet to be fully elucidated.

METHODS

Utilizing linkage disequilibrium score regression (LDSC) and bidirectional two-sample univariable Mendelian Randomization (UVMR) analyses with large-scale GWAS datasets, we investigated the genetic correlations and causal associations across six sleep traits and 24 prevalent brain disorders. Additionally, a multivariable Mendelian Randomization (MVMR) analysis evaluated the cumulative effects of various sleep traits on each brain disorder, complemented by genetic loci characterization to pinpoint pertinent genes and pathways.

RESULTS

LDSC analysis identified significant genetic correlations in 66 out of 144 (45.8 %) pairs between sleep-related traits and brain disorders, with the most pronounced correlations observed in psychiatric disorders (66 %, 48/72). UVMR analysis identified 29 causal relationships (FDR<0.05) between sleep traits and brain disorders, with 19 associations newly discovered according to our knowledge. Notably, major depression, attention-deficit/hyperactivity disorder, bipolar disorder, cannabis use disorder, and anorexia nervosa showed bidirectional causal relations with sleep traits, especially insomnia's marked influence on major depression (IVW beta 0.468, FDR = 5.24E-09). MVMR analysis revealed a nuanced interplay among various sleep traits and their impact on brain disorders. Genetic loci characterization underscored potential genes, such as HOXB2, while further enrichment analyses illuminated the importance of synaptic processes in these relationships.

CONCLUSIONS

This study provides compelling evidence for the causal relationships and shared genetic backgrounds between common sleep-related traits and brain disorders.

Assessing the associations of 1,400 blood metabolites with major depressive disorder: a Mendelian randomization study

Background and objectives

Major Depressive Disorder (MDD) is one of the most prevalent and debilitating health conditions worldwide. Previous studies have reported a link between metabolic dysregulation and MDD. However, evidence for a causal relationship between blood metabolites and MDD is lacking.

Methods

Using a two-sample bidirectional Mendelian randomization analysis (MR), we assessed the causal relationship between 1,400 serum metabolites and Major Depressive Disorder (MDD). The Inverse Variance Weighted method (IVW) was employed to estimate the causal association between exposures and outcomes. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode methods were used as supplementary approaches for a comprehensive appraisal of the causality between blood metabolites and MDD. Pleiotropy and heterogeneity tests were also conducted. Lastly, the relevant metabolites were subjected to metabolite function analysis, and a reverse MR was implemented to explore the potential influence of MDD on these metabolites.

Results

After rigorous screening, we identified 34 known metabolites, 13 unknown metabolites, and 18 metabolite ratios associated with Major Depressive Disorder (MDD). Among all metabolites, 33 were found to have positive associations, and 32 had negative associations. The top five metabolites that increased the risk of MDD were the Arachidonate (20:4n6) to linoleate (18:2n6) ratio, LysoPE(18:0/0:0), N-acetyl-beta-alanine levels, Arachidonate (20:4n6) to oleate to vaccenate (18:1) ratio, Glutaminylglutamine, and Threonine to pyruvate ratio. Conversely, the top five metabolites that decreased the risk of MDD were N6-Acetyl-L-lysine, Oleoyl-linoleoyl-glycerol (18:1 to 18:2) [2] to linoleoyl-arachidonoyl-glycerol (18:2 to 20:4) [2] ratio, Methionine to phosphate ratio, Pregnanediol 3-O-glucuronide, and 6-Oxopiperidine-2-carboxylic acid. Metabolite function enrichment was primarily concentrated in pathways such as Bile Acid Biosynthesis (FDR=0.177), Glutathione Metabolism (FDR=0.177), Threonine, and 2-Oxobutanoate Degradation (FDR=0.177). In addition, enrichment was noted in pathways like Valine, Leucine, and Isoleucine Biosynthesis (p=0.04), as well as Ascorbate and Aldarate Metabolism (p=0.04).

Discussion

Within a pool of 1,400 blood metabolites, we identified 34 known metabolites and 13 unknown metabolites, as well as 18 metabolite ratios associated with Major Depressive Disorder (MDD). Additionally, three functionally enriched groups and two metabolic pathways were selected. The integration of genomics and metabolomics has provided significant insights for the screening and prevention of MDD.

Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data

BACKGROUND

Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown.

METHODS

We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method.

FINDINGS

The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms.

INTERPRETATION

Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively.

FUNDING

Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.

Association between mild depressive states in polycystic ovary syndrome and an unhealthy lifestyle

Objective

Polycystic Ovary Syndrome (PCOS) is a prevalent and frequently encountered gynecological disorder. Its high variability and the complexities associated with its management often lead to psychological stress in affected women, manifesting in symptoms of depression. Embracing a healthy lifestyle is fundamental in PCOS treatment. Consistent adherence to a healthy lifestyle not only aids in improving PCOS symptoms but also plays a role in enhancing mental well-being. However, there is currently limited research examining the extent of depression, its prevalence, and its correlation with lifestyle among individuals with PCOS. Therefore, this study aims to explore the impact of lifestyle factors on the depressive state of individuals with PCOS.

Methods

This cross-sectional study gathered data from 411 individuals with PCOS at a comprehensive hospital in Henan, China. Depression status was assessed using the Hamilton Depression Scale, and demographic information as well as lifestyle habits were simultaneously collected. Univariate and multivariate analyses using logistic regression were conducted to identify risk factors associated with the depressive state in PCOS.

Results

Among the surveyed 411 individuals with PCOS, approximately 49.4% exhibited symptoms of depression, with 83.7% experiencing mild depressive symptoms. A disease duration of 1-3 years, the presence of acne, and unhealthy lifestyle factors such as high-fat diet, staying up late, lack of exercise, and mental stress emerged as significant risk factors for the onset of depressive symptoms.

Conclusion

Depressive symptoms in individuals with PCOS are predominantly mild. The risk of comorbid depression in PCOS is associated with the presence of acne, frequent high-fat diet, regular staying up late, lack of exercise, and mental stress.

Association between abnormal default mode network homogeneity and sleep disturbances in major depressive disorder

Background

Sleep disturbance is a common comorbidity of major depressive disorder (MDD). However, network homogeneity (NH) changes of the default mode network (DMN) in MDD with sleep disturbances are unclear.

Aims

The purpose of this study was to probe the abnormal NH in the DMN in MDD with sleep disturbances and to reveal the differences between MDD with or without sleep disturbances.

Methods

Twenty-four patients with MDD and sleep disturbances (Pa_s), 33 patients with MDD without sleep disturbances (Pa_ns) and 32 healthy controls (HCs) were recruited in this study. Resting-state functional imaging data were analysed using NH.

Results

Compared with Pa_ns and HCs, Pa_s showed decreased NH in the left superior medial prefrontal cortex and increased NH in the right precuneus. There was a negative correlation between NH in the left superior medial prefrontal cortex and sleep disturbances (r=-0.42, p=0.001) as well as a positive correlation between NH in the right precuneus and sleep disturbances (r=0.41, p=0.002) in patients with MDD.

Conclusions

MDD with sleep disturbances is associated with abnormal NH in the DMN, which could differentiate pa_s from pa_ns. The DMN may play a crucial role in the neurobiological mechanisms of MDD with sleep disturbances.

Clinical Phenotypes Supporting the Relationship Between Sleep Disturbance and Impairment of Placebo Effects

Lack of good sleep or insomnia can lead to many health issues, including an elevated risk of cardiovascular disease, obesity, fatigue, low mood, and pain. While chronic pain negatively impacts sleep quality, the relationship between descending pain modulatory systems like placebo effects and sleep quality is not thoroughly known. We addressed this aspect in a cross-sectional study in participants with chronic pain. Placebo effects were elicited in a laboratory setting using thermal heat stimulations delivered with visual cues using classical conditioning and verbal suggestions. We estimated the levels of insomnia severity with the Insomnia Severity Index and the sleep quality with the Pittsburg Sleep Quality Index. The previous night's sleep continuity was assessed as total sleep time, sleep efficiency, and sleep midpoint the night before the experiment. 277 people with chronic pain and 189 pain-free control individuals participated. Participants with chronic pain and insomnia showed smaller placebo effects than those with chronic pain without insomnia. Similarly, poor sleep quality was associated with reduced placebo effects among participants with chronic pain. Clinical anxiety measured by Depression Anxiety Stress Scales partially mediated these effects. In contrast, placebo effects were not influenced by the presence of insomnia or poor sleep quality in pain-free participants. Sleep continuity the night before the experiment did not influence the placebo effects. Our results indicate that participants who experience insomnia and/or poor sleep quality and chronic pain have smaller placebo effects, and that the previous night sleep continuity does not influence the magnitude of placebo effects. PERSPECTIVE: This study examined the relationship between sleep disturbances and experimentally induced placebo effects. We found that individuals with chronic pain who experience insomnia and poor sleep quality demonstrated reduced placebo effects compared to their counterparts with good sleep quality and no insomnia.

The sleep-circadian interface: A window into mental disorders

Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep-circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep-circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.

Potential Role of Bmal1 in Lipopolysaccharide-Induced Depression-Like Behavior and its Associated "Inflammatory Storm"

Inflammation plays an important role in the pathogenesis of depression; however, the underlying mechanisms remain unclear. Apart from the disordered circadian rhythm in animal models and patients with depression, dysfunction of clock genes has been reported to be involved with the progress of inflammation. This study aimed to investigate the role of circadian clock genes, especially brain and muscle ARNT-like 1 (Bmal1), in the linkage between inflammation and depression. Lipopolysaccharide (LPS)-challenged rats and BV2 cells were used in the present study. Four intraperitoneal LPS injections of 0.5 mg/kg were administered once every other day to the rats, and BV2 cells were challenged with LPS for 24 h at the working concentration of 1 mg/L, with or without the suppression of Bmal1 via small interfering RNA. The results showed that LPS could successfully induce depression-like behaviors and an "inflammatory storm" in rats, as indicated by the increased immobility time in the forced swimming test and the decreased saccharin preference index in the saccharin preference test, together with hyperactivity of the hypothalamic-pituitary-adrenal axis, hyperactivation of astrocyte and microglia, and increased peripheral and central abundance of tumor necrosis factor-α, interleukin 6, and C-reactive protein. Moreover, the protein expression levels of brain-derived neurotrophic factor, triggering receptor expressed on myeloid cells 1, Copine6, and Synaptotagmin1 (Syt-1) decreased in the hippocampus and hypothalamus, whereas the expression of triggering receptor expressed on myeloid cells 2 increased. Interestingly, the fluctuation of temperature and serum concentration of melatonin and corticosterone was significantly different between the groups. Furthermore, protein expression levels of the circadian locomotor output cycles kaput, cryptochrome 2, and period 2 was significantly reduced in the hippocampus of LPS-challenged rats, whereas Bmal1 expression was significantly increased in the hippocampus but decreased in the hypothalamus, where it was co-located with neurons, microglia, and astrocytes. Consistently, apart from the reduced cell viability and increased phagocytic ability, LPS-challenged BV2 cells presented a similar trend with the changed protein expression in the hippocampus of the LPS model rats. However, the pathological changes in BV2 cells induced by LPS were reversed after the suppression of Bmal1. These results indicated that LPS could induce depression-like pathological changes, and the underlying mechanism might be partly associated with the imbalanced expression of Bmal1 and its regulated dysfunction of the circadian rhythm.

Neuropsychiatric disorders, chronotype and sleep: A narrative review of GWAS findings and the application of Mendelian randomization to investigate causal relationships

Genome-wide association studies (GWAS) have been important for characterizing the genetic component and enhancing our understanding of the biological aetiology of both neuropsychiatric disorders and sleep-related phenotypes such as chronotype, which is our preference for morning or evening time. Mendelian randomization (MR) is a post-GWAS analysis that is used to infer causal relationships between potential risk factors and outcomes. MR uses genetic variants as instrumental variants for exposures to study the effect on outcomes. This review details the main results from GWAS of neuropsychiatric disorders and sleep-related phenotypes, and the application of MR to investigate their bidirectional relationship. The main results from MR studies of neuropsychiatric disorders and sleep-related phenotypes are summarized. These MR studies have identified 37 causal relationships between neuropsychiatric disorders and sleep-related phenotypes. MR studies identified evidence of a causal role for five neuropsychiatric disorders and symptoms (attention deficit hyperactivity disorder, bipolar disorder, depressive symptoms, major depressive disorder and schizophrenia) on sleep-related phenotypes and evidence of a causal role for five sleep-related phenotypes (daytime napping, insomnia, morning person, long sleep duration and sleep duration) on risk for neuropsychiatric disorders. These MR results show a bidirectional relationship between neuropsychiatric disorders and sleep-related phenotypes and identify potential risk factors for follow-up studies.

Relationship between biological rhythm dysregulation and suicidal ideation in patients with major depressive disorder

BACKGROUND

Although the disturbance of circadian rhythms represents a significant clinical feature of major depressive disorder (MDD), the relationship between biological rhythm disturbances and the severity of suicidal ideation in individuals with MDD remains unclear. We aimed to explore the characteristics of different biological rhythm dimensions in MDD and their association with the severity of depressive symptoms and suicidal ideation.

METHODS

A total of 50 MDD patients and 50 healthy controls were recruited and their general information was collected. The severity of depressive symptoms was assessed with the 17-item Hamilton Depression Rating Scale (HDRS17). The intensity of suicidal ideation was evaluated with the Beck Scale for Suicide Ideation (BSS). The Chinese version of the Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN) scale was utilized to assess the participants' biological rhythm dysregulation. Multiple logistic regression analysis was conducted to explore the relationship between biological rhythm and the risk of MDD. Multiple linear regression analysis was performed in the MDD group to investigate the relationship between different biological rhythm dimensions and suicide ideation.

RESULTS

Significant differences were observed between the MDD group and the control group in total BRIAN score (Z=-5.41, P < 0.001) as well as scores for each dimension. After adjusting for confounding factors, multiple logistic regression analysis revealed a significant association between total BRIAN score and the presence of MDD (OR = 1.20, 95% CI = 1.10-1.29, P < 0.001), as well as between scores in different BRIAN dimensions and the presence of MDD (activity: OR = 1.47, 95% CI = 1.24-1.74, P < 0.001; sleep: OR = 1.52, 95% CI = 1.28-1.79, P < 0.001; social: OR = 1.80, 95% CI = 1.32-2.46, P < 0.001; eating pattern: OR = 1.34, 95% CI = 1.12-1.60, P = 0.001). In patients with MDD, linear regression analysis demonstrated a positive relationship between BSS scores and BRIAN eating pattern scores (β = 0.34, P = 0.022), even after adjusting for demographic factors and the severity of depression.

CONCLUSIONS

Patients with MDD exhibited significantly higher levels of dysregulation in all four biological rhythm dimensions compared to healthy controls and the degree of dysregulation was associated with the severity of depression. More importantly, dysregulation of eating pattern may increase the intensity of suicidal ideation in MDD, thus elevating the risk of suicide.

The Role of Circadian Rhythms and Sleep in Anorexia Nervosa

Importance

Observational studies have associated anorexia nervosa with circadian rhythms and sleep traits. However, the direction of causality and the extent of confounding by psychosocial comorbidities in these associations are unknown.

Objectives

To investigate the association between anorexia nervosa and circadian and sleep traits through mendelian randomization and to test the associations between a polygenic risk score (PRS) for anorexia nervosa and sleep disorders in a clinical biobank.

Design, Setting, and Participants

This genetic association study used bidirectional 2-sample mendelian randomization with summary-level genetic associations between anorexia nervosa (from the Psychiatric Genomics Consortium) and chronotype and sleep traits (primarily from the UK Biobank). The inverse-variance weighted method, in addition to other sensitivity approaches, was used. From the clinical Mass General Brigham (MGB) Biobank (n = 47 082), a PRS for anorexia nervosa was calculated for each patient and associations were tested with prevalent sleep disorders derived from electronic health records. Patients were of European ancestry. All analyses were performed between February and August 2023.

Exposures

Genetic instruments for anorexia nervosa, chronotype, daytime napping, daytime sleepiness, insomnia, and sleep duration.

Main Outcomes and Measures

Chronotype, sleep traits, risk of anorexia nervosa, and sleep disorders derived from a clinical biobank.

Results

The anorexia nervosa genome-wide association study included 16 992 cases (87.7%-97.4% female) and 55 525 controls (49.6%-63.4% female). Genetic liability for anorexia nervosa was associated with a more morning chronotype (β = 0.039; 95% CI, 0.006-0.072), and conversely, genetic liability for morning chronotype was associated with increased risk of anorexia nervosa (β = 0.178; 95% CI, 0.042-0.315). Associations were robust in sensitivity and secondary analyses. Genetic liability for insomnia was associated with increased risk of anorexia nervosa (β = 0.369; 95% CI, 0.073-0.666); however, sensitivity analyses indicated bias due to horizontal pleiotropy. The MGB Biobank analysis included 47 082 participants with a mean (SD) age of 60.4 (17.0) years and 25 318 (53.8%) were female. A PRS for anorexia nervosa was associated with organic or persistent insomnia in the MGB Biobank (odds ratio, 1.10; 95% CI, 1.03-1.17). No associations were evident for anorexia nervosa with other sleep traits.

Conclusions and Relevance

The results of this study suggest that in contrast to other metabo-psychiatric diseases, anorexia nervosa is a morningness eating disorder and further corroborate findings implicating insomnia in anorexia nervosa. Future studies in diverse populations and with subtypes of anorexia nervosa are warranted.

Prevalence and predictors for postpartum sleep disorders: a nationwide analysis

OBJECTIVE

To describe the prevalence and predictors of postpartum sleep disorders.

DESIGN

A retrospective cohort study.

SETTING

Postpartum.

POPULATION

Commercially insured women delivering in California (USA) between 2011 and 2014.

METHODS

Using the Optum Clinformatics Datamart Database.

MAIN OUTCOME MEASURES

Prevalence of a postpartum sleep disorder diagnosis with and without a depression diagnosis up to 12 months following hospital discharge for inpatient delivery. We also identified predictors of a postpartum sleep disorder diagnosis using multivariable logistic regression.

RESULTS

We identified 3535 (1.9%) women with a postpartum sleep disorder diagnosis. The prevalence of sleep disorder diagnoses was insomnia (1.3%), sleep apnea (0.25%), and other sleep disorder (0.25%). The odds of a postpartum sleep disorder were highest among women with a history of drug abuse (adjusted odds ratio (aOR): 2.70, 95% confidence interval (CI): 1.79-4.09); a stillbirth delivery (aOR: 2.15, 95% CI: 1.53-3.01); and chronic hypertension (aOR: 1.82; 95% CI: 1.57-2.11). A comorbid diagnosis of a postpartum sleep disorder and depression occurred in 1182 women (0.6%). These women accounted for 33.4% of all women with a postpartum sleep disorder. The strongest predictors of a comorbid diagnosis were a history of drug abuse (aOR: 4.13; 95% CI: 2.37-7.21) and a stillbirth delivery (aOR: 2.93; 95% CI: 1.74-4.92).

CONCLUSIONS

Postpartum sleep disorders are underdiagnosed conditions, with only 2% of postpartum women in this cohort receiving a sleep diagnosis using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes. Insomnia was the most common disorder and one-third of women diagnosed with a postpartum sleep disorder had a co-morbid diagnosis of depression. Future studies are needed to improve the screening and diagnostic accuracy of postpartum sleep disorders.

Selection of genetic instruments in Mendelian randomisation studies of sleep traits

This review explores the criteria used for the selection of genetic instruments of sleep traits in the context of Mendelian randomisation studies. This work was motivated by the fact that instrument selection is the most important decision when designing a Mendelian randomisation study. As far as we are aware, no review has sought to address this to date, even though the number of these studies is growing rapidly. The review is divided into the following sections which are essential for genetic instrument selection: 1) Single-gene region vs polygenic analysis; 2) Polygenic analysis: biologically-vs statistically-driven approaches; 3) P-value; 4) Linkage disequilibrium clumping; 5) Sample overlap; 6) Type of exposure; 7) Total (R2) and average strength (F-statistic) metrics; 8) Number of single-nucleotide polymorphisms; 9) Minor allele frequency and palindromic variants; 10) Confounding. Our main aim is to discuss how instrumental choice impacts analysis and compare the strategies that Mendelian randomisation studies of sleep traits have used. We hope that our review will enable more researchers to take a more considered approach when selecting genetic instruments for sleep exposures.

The relations between chronotype, stressful life events, and impulsivity in the Adolescent Brain Cognitive Development (ABCD) study

Circadian rhythm disturbances, especially circadian phase delays are associated with impulsive behaviors and have been implicated in psychiatric disorders. Chronotype is a developmentally regulated proxy measure of circadian phase. Past studies have investigated the relationship between chronotype and trauma and found that trauma is associated with evening chronotypes, suggesting the course of chronotype development may be affected by adverse childhood experiences (ACEs). However, the relationships among chronotype, impulsivity and ACEs have largely been studied in a pairwise manner using small, cross-sectional cohorts. We hypothesized that in a cohort of high-risk youth, childhood trauma would be associated with later chronotype, and later chronotype would be associated with higher rates of impulsivity. We analyzed a cross-sectional sample (n = 966) from Year 2 of adolescents at high risk for psychiatric disorders from the ABCD study who were characterized for chronotype, stressful life events, and impulsivity. We used a hierarchical regression model to examine the relationship between chronotype, stressful life events, and impulsivity using the Munich Chronotype Questionnaire (MCTQ), the Life Events Scale, Urgency, Premeditation, Perseverance and Sensation Seeking (UPPS) Impulsive Behavior scale. We found associations between eveningness, stressful life events, and all dimensions of impulsivity. Increased eveningness was associated with a higher number of stressful life events and increased impulsivity. Understanding the role of stressful life events and impulsivity in those predisposed towards eveningness is useful because it may improve our understanding of the biological mechanisms that contribute to psychiatric disorders, and lead to better prevention and treatment efforts using interventions such as increased lifestyle regularity and daytime light exposure.

Nonlinear relationship between sleep midpoint and depression symptoms: a cross-sectional study of US adults

BACKGROUND

Despite the close relationship between sleep-wake cycles and depression symptoms, the relationship between sleep midpoint and depression symptoms in adults remains understudied.

METHODS

In this cross-sectional study, 18280 adults aged ≥ 18 years from the National Health and Nutrition Examination Survey (NHANES) 2015-2020 were analyzed. Covariates included age, sex, race/ethnicity, education level, marital status, family income, body mass index, smoking status, drinking status, physical activity, comorbid condition, sleep duration, and sleep disturbance were adjusted in multivariate regression models.

RESULTS

Weighted restricted cubic spline based on the complex sampling design of NHANES showed that in participants with a sleep midpoint from 2:18 AM to 6:30 AM, the prevalence of depression symptoms increased by 0.2 times (adjusted odds ratio [OR] = 1.20, 95% confidence interval [CI]: 1.08-1.33) per 1-h increment in sleep midpoint compared to the reference point of 2:18 AM. For participants with a sleep midpoint after 6:30 AM and before 2:18 AM the next day, the relationship between sleep midpoint and depression symptoms was not significant after adjusting for all covariates (adjusted OR = 1.01, 95% CI: 0.99-1.03).

CONCLUSIONS

The findings indicate a significant nonlinear association between sleep midpoint and depression symptoms in a nationally representative sample of adults.

Modifiable risk factors of major depressive disorder: A Mendelian randomization study

Identifying modifiable risk factors early on is essential to prevent major depressive disorder (MDD). This study systematically investigated the causal relationship between 19 modifiable risk factors and MDD. Single-nucleotide polymorphisms (SNPs) associated with 19 potentially modifiable risk factors were screened via the genome-wide association study (GWAS) enrolling individuals of European descent. Summary-level data for MDD (59,851 cases and 113,154 controls) were extracted from the UK Biobank. The inverse-variance-weighted (IVW) method was utilized as the primary analysis. Sensitivity analyses were performed using the MR-Egger method, the Maximum likelihood method, the MR-pleiotropy residual sum outlier (MR-PRESSO) method, and MR-robust adjusted profile score (MR-RAPS) method. MR-Egger regression, heterogeneity tests, pleiotropy tests, and leave-one-out tests were also performed to analyze sensitivity. The MR Steiger test was used to verify the directionality of the exposure to the outcome. Genetically predicted smoking initiation increased the risk of MDD (P = 6.00E-09), while smoking status: never and past tobacco smoking decreased the risk of MDD (all P < 0.01). In addition, education level was inversely associated with MDD risk (all P < 0.01). Genetically instrumented sleeplessness/insomnia, daytime naps, and nap during the day were positively related to the risk of MDD (all P < 0.01). Personal feelings, including guilt, hurt, tension, and worry too long after an embarrassing experience, had a suggestive increased risk for MDD (all P < 0.000). The remaining five modifiable risk factors were all causally associated with the risk of MDD, including neuroticism, neuroticism scores, body mass index (BMI), average total household income before tax, and types of physical activity in the last 4 weeks (all P < 0.01). All 19 potentially modifiable risk factors were causally associated with the risk of MDD. The main hypothesis of this MR study was that identifying and intervening in these 19 potentially modifiable risk factors could be beneficial to the prevention and treatment of MDD and further reduce mortality and economic burden.

Sleep and its association with depressive and anxiety symptoms during the last weeks of pregnancy: A population-based study

OBJECTIVE

To evaluate the association between sleep characteristics and depressive and anxiety symptoms during the immediate postpartum period.

METHODS

People who had hospital births during 2019 in the municipality of Rio Grande (southern Brazil) were assessed with a standardized questionnaire concerning sociodemographic (eg, age and self-reported skin color) and health-related variables (eg, parity and stillbirth) (n = 2314) 24-48 hours after birth. We used the Munich Chronotype Questionnaire to assess sleep latency, inertia, duration, and chronotype; the Edinburgh Postpartum Depression Scale for depressive symptoms; and the General Anxiety Disorder 7-Item Scale to evaluate anxiety symptoms. We used logistic regression models to calculate odds ratios.

RESULTS

The prevalence of depressive symptoms was 13.7%, and of anxiety symptoms was 10.7%. Depressive symptoms were more likely in those with vespertine chronotype (odds ratios = 1.63; 95% CI: 1.14-2.35) and those with a sleep latency of more than 30 minutes (OR = 2.36; 95% CI: 1.68-3.32). The probability of depressive symptoms decreased by 16% for each additional hour of sleep (OR = 0.84; 95% CI: 0.77-0.92). Sleep inertia of 11-30 minutes increased the probability of anxiety on free days (OR = 1.73; 95% CI: 1.27-2.36) and increased the probability of depressive (OR = 2.68; 95% CI: 1.82-3.83) and anxiety symptoms (OR = 1.69; 95%CI: 1.16-2.44) on workdays.

CONCLUSION

Participants with vespertine chronotype or shorter sleep duration were more likely to have depressive symptoms. Those who took more time to fall asleep or get out of bed were more likely to have both anxiety and depressive symptoms, but the association was stronger for depressive symptoms.

Four modifiable factors that mediate the effect of educational time on major depressive disorder risk: A network Mendelian randomization study

BACKGROUND

Major depressive disorder (MDD) is a mental illness, which is a notable public health problem that aggravates the global economic burden. This study aimed to investigate the causal relationship between education and MDD risk and the contributions of effects mediated by four modifiable factors.

MATERIALS AND METHODS

Instrumental variables were screened from several large-scale genome-wide association study (GWAS) data (years of schooling with 766,345 participants, MDD with 59,851 cases and 113,154 controls, neuroticism with 329,821 individuals, smoking behavior with 195,068 cases and 164,638 controls, body mass index [BMI] with 336,107 individuals, and household income with 397,751 individuals). The data were used to evaluate the association of the four modifiable factors (neuroticism, smoking behavior, BMI, and household income) that mediate the effect of education on MDD risk via Mendelian randomization (MR) analysis.

RESULTS

Each standard deviation increase in years of schooling could reduce the risk for MDD by 30.70%. Higher neuroticism and BMI were associated with a higher risk of MDD. Non-smoking status and increased household income were protective factors for MDD. Notably, the mediator neuroticism, BMI, smoking behavior, and household income explained 52.92%, 15.54%, 31.86%, and 81.30% of the effect of years of schooling on MDD risk, respectively.

CONCLUSIONS

Longer years of schooling have a protective effect on MDD risk. Reasonable interventions to reduce neuroticism, BMI, smoking, and increasing household income are beneficial for MDD prevention. Our work provides new ideas for the development of prevention strategies for MDD.

Objectively assessed sleep and physical activity in depression subtypes and its mediating role in their association with cardiovascular risk factors

The aims of this study were to investigate the associations of major depressive disorder (MDD) and its subtypes (atypical, melancholic, combined, unspecified) with actigraphy-derived measures of sleep, physical activity and circadian rhythms; and test the potentially mediating role of sleep, physical activity and circadian rhythms in the well-established associations of the atypical MDD subtype with Body Mass Index (BMI) and the metabolic syndrome (MeS). The sample consisted of 2317 participants recruited from an urban area, who underwent comprehensive somatic and psychiatric evaluations. MDD and its subtypes were assessed via semi-structured diagnostic interviews. Sleep, physical activity and circadian rhythms were measured using actigraphy. MDD and its subtypes were associated with several actigraphy-derived variables, including later sleep midpoint, low physical activity, low inter-daily stability and larger intra-individual variability of sleep duration and relative amplitude. Sleep midpoint and physical activity fulfilled criteria for partial mediation of the association between atypical MDD and BMI, and physical activity also for partial mediation of the association between atypical MDD and MeS. Our findings confirm associations of MDD and its atypical subtype with sleep and physical activity, which are likely to partially mediate the associations of atypical MDD with BMI and MeS, although most of these associations are not explained by sleep and activity variables. This highlights the need to consider atypical MDD, sleep and sedentary behavior as cardiovascular risk factors.

Causal relationship between nonalcoholic fatty liver disease and different sleep traits: a bidirectional Mendelian randomized study

Background and aims

Non-alcoholic fatty liver disease(NAFLD) is common worldwide and has previously been reported to be associated with sleep traits. However, it is not clear whether NAFLD changes sleep traits or whether the changes in sleep traits lead to the onset of NAFLD. The purpose of this study was to investigate the causal relationship between NAFLD and changes in sleep traits using Mendelian randomization.

Methods

We proposed a bidirectional Mendelian randomization (MR) analysis and performed validation analyses to dissect the association between NAFLD and sleep traits. Genetic instruments were used as proxies for NAFLD and sleep. Data of genome-wide association study(GWAS) were obtained from the center for neurogenomics and cognitive research database, Open GWAS database and GWAS catalog. Three MR methods were performed, including inverse variance weighted method(IVW), MR-Egger, weighted median.

Results

In total,7 traits associated with sleep and 4 traits associated with NAFLD are used in this study. A total of six results showed significant differences. Insomnia was associated with NAFLD (OR(95% CI)= 2.25(1.18,4.27), P = 0.01), Alanine transaminase levels (OR(95% CI)= 2.79(1.70, 4.56), P =4.71×10-5) and percent liver fat(OR(95% CI)= 1.31(1.03,1.69), P = 0.03). Snoring was associated with percent liver fat (1.15(1.05,1.26), P =2×10-3), alanine transaminase levels (OR(95% CI)= 1.27(1.08,1.50), P =0.04).And dozing was associated with percent liver fat(1.14(1.02,1.26), P =0.02).For the remaining 50 outcomes, no significant or definitive association was yielded in MR analysis.

Conclusion

Genetic evidence suggests putative causal relationships between NAFLD and a set of sleep traits, indicating that sleep traits deserves high priority in clinical practice. Not only the confirmed sleep apnea syndrome, but also the sleep duration and sleep state (such as insomnia) deserve clinical attention. Our study proves that the causal relationship between sleep characteristics and NAFLD is the cause of the change of sleep characteristics, while the onset of non-NAFLD is the cause of the change of sleep characteristics, and the causal relationship is one-way.

Critically-timed sleep+light interventions differentially improve mood in pregnancy vs. postpartum depression by shifting melatonin rhythms

BACKGROUND

Testing the hypothesis that combined wake + light therapy improves mood in pregnant vs. postpartum depressed participants (DP) by differentially altering melatonin and sleep timing.

METHODS

Initially 89 women, 37 pregnant (21 normal controls-NC; 16 DP) and 52 postpartum (27 NCs; 25 DP), were randomized to a parallel trial of a phase-delay intervention (PDI): 1-night of early-night wake therapy (sleep 3-7 am) + 6-weeks of evening bright white light (Litebook Advantage) for 60 min starting 90 min before bedtime, vs. a Phase-advance intervention (PAI): 1-night of late-night wake therapy (sleep 9 pm-1 am) + 6-weeks of morning bright white light for 60 min within 30 min of wake time. Blinded clinicians assessed mood weekly by structured interview, and participants completed subjective ratings, a Morningness-Eveningness questionnaire, actigraphy, and collected 2 overnight urine samples for 6-sulphatoxy melatonin (6-SMT).

RESULTS

In pregnant DP, mood improved more after the PDI vs. PAI (p = .016), whereas in postpartum DP, mood improved more after the PAI vs. PDI (p = .019). After wake therapy, 2 weeks of light treatment was as efficacious as 6 weeks (p > .05). In postpartum DP, PAI phase-advanced 6-SMT offset and acrophase (p < .05), which correlated positively with mood improvement magnitude (p = .003).

LIMITATIONS

Small N.

CONCLUSIONS

Mood improved more after 2 weeks of the PDI in pregnant DP, but more after 2 weeks of PAI in postpartum DP in which improvement magnitude correlated with 6-SMT phase-advance. Thus, critically-timed Sleep + Light Interventions provide safe, efficacious, rapid-acting, well-tolerated, at-home, non-pharmaceutical treatments for peripartum DP.

Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans

During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.

Seasonality of brain function: role in psychiatric disorders

Seasonality patterns are reported in various psychiatric disorders. The current paper summarizes findings on brain adaptations associated with seasonal changes, factors that contribute to individual differences and their implications for psychiatric disorders. Changes in circadian rhythms are likely to prominently mediate these seasonal effects since light strongly entrains the internal clock modifying brain function. Inability of circadian rhythms to accommodate to seasonal changes might increase the risk for mood and behavior problems as well as worse clinical outcomes in psychiatric disorders. Understanding the mechanisms that account for inter-individual variations in seasonality is relevant to the development of individualized prevention and treatment for psychiatric disorders. Despite promising findings, seasonal effects are still understudied and only controlled as a covariate in most brain research. Rigorous neuroimaging studies with thoughtful experimental designs, powered sample sizes and high temporal resolution alongside deep characterization of the environment are needed to better understand the seasonal adaptions of the human brain as a function of age, sex, and geographic latitude and to investigate the mechanisms underlying the alterations in seasonal adaptation in psychiatric disorders.

Genetics of circadian rhythms and sleep in human health and disease

Circadian rhythms and sleep are fundamental biological processes integral to human health. Their disruption is associated with detrimental physiological consequences, including cognitive, metabolic, cardiovascular and immunological dysfunctions. Yet many of the molecular underpinnings of sleep regulation in health and disease have remained elusive. Given the moderate heritability of circadian and sleep traits, genetics offers an opportunity that complements insights from model organism studies to advance our fundamental molecular understanding of human circadian and sleep physiology and linked chronic disease biology. Here, we review recent discoveries of the genetics of circadian and sleep physiology and disorders with a focus on those that reveal causal contributions to complex diseases.

Association between reading and depression in Chinese adults

Qualitative evidences have shown that having the habit of reading might be beneficial for mental health. The present study aims to examine the relationship between reading and depression. National cross-sectional survey data of adults aged >40 years in mainland China were used. The Center for Epidemiological Studies Depression Scale questionnaire was utilized to detect depression status. Multilevel binary logistic and linear regression models were employed to reveal the association, and restricted cubic spline with 4 knots was adopted to describe the non-linear association of reading quantity and depression. The prevalence of depression was 13.02% in the target population. It was found that the habit of reading was negatively associated with depression, the odds ratio was 0.809 (95% confidence interval: 0.657-0.997). Diverse association between reading and depression was observed in different age groups, and a significant association was identified among the elderly, but not in the middle-aged population. Restricted cubic spline showed several books read per year might lower the risk of depression and 20-items Center for Epidemiological Studies Depression Scale score. A lower prevalence of depression was observed in the target population. The habit of reading was negatively associated with depression. Age-specific association was observed. It is worth paying attention to the reading habit that could be beneficial in the elderly for mental health intervention, but it needs to be confirmed by experimental study.

Evaluation of Sleep Habits and Disturbances Among US Adults, 2017-2020

IMPORTANCE

Unhealthy sleep behaviors and sleep disturbances are associated with higher risk of multiple diseases and mortality. The current profiles of sleep habits and disturbances, particularly the differences between workdays and free days, are unknown in the contemporary US.

OBJECTIVE

To comprehensively evaluate sleep habits on workdays and free days and the prevalence of sleep disturbances among US adults.

DESIGN, SETTING, AND PARTICIPANTS

This study is a cross-sectional analysis of US nationally representative data from the National Health and Nutrition Examination Survey (2017-2020) among adults aged 20 years or older. Data analysis was performed from February to May 2022.

MAIN OUTCOMES AND MEASURES

The main outcomes were means and/or distributions of sleep habits, including sleep duration and sleep-wake timing on workdays and free days, sleep debt (ie, the difference between sleep duration on free days and mean weekly sleep duration), and social jet lag (ie, the difference between the midpoint between sleep and wake time on workdays and free days). Prevalence of trouble sleeping (ie, participants told a doctor or other health professional that they have trouble sleeping) and daytime sleepiness (ie, self-reported feeling of being overly sleepy during the day ≥5 times per month) were also determined.

RESULTS

A total of 9004 individuals (mean [SE] age, 48.3 [0.53] years; 4635 women [51.9%]; 3158 non-Hispanic White [62.8%]) were included in the current study. The mean sleep duration was 7.59 hours (95% CI, 7.54 to 7.64 hours) on workdays and 8.24 hours (95% CI, 8.17 to 8.31 hours) on free days (difference, 0.65 hour). The mean sleep and wake times were at 11:02 pm (95% CI, 10:57 pm to 11:17 pm) and 6:41 am (95% CI, 6:36 am to 6:45 am), respectively, on workdays and 11:25 pm (95% CI, 11:21 pm to 11:35 pm) and 7:41 am (95% CI, 7:37 am to 7:46 am), respectively, on free days (differences, 0.23 hour for sleep time and 1.00 hour for wake time). On workdays, 23.1% (95% CI, 21.3% to 24.9%) of adults slept less than 7 hours and 25.4% (95% CI, 24.1% to 26.6%) went to sleep at midnight or later; the corresponding percentages changed to 12.9% (95% CI, 11.6% to 14.1%) and 40.9% (95% CI, 38.4% to 43.5%), respectively, on free days. Furthermore, the mean sleep debt was 0.73 hours (95% CI, 0.68 to 0.77 hours), and mean social jet lag was 1.10 hours (95% CI, 1.05 to 1.15 hours); 30.5% (95% CI, 26.8% to 33.3%) of adults experienced 1 hour or more of sleep debt, and 46.5% (95% CI, 42.6% to 50.3%) experienced 1 hour or more of social jet lag. The prevalence of trouble sleeping was 29.8% (95% CI, 28.2% to 31.5%), and that of daytime sleepiness was 27.2% (95% CI, 25.0% to 29.5%).

CONCLUSIONS AND RELEVANCE

In 2017 to 2020, US adults showed variability in sleep habits between workdays and free days, with longer sleep duration and later sleep-wake phases on free days, and high percentages of US adults experienced long-term sleep deprivation, chronic social jet lag, and frequent sleep disturbances. These findings provide evidence to further investigate potential approaches to optimize overall US sleep health.

The relationship between morningness-eveningness and mood symptoms and quality of life in euthymic state of mood disorders: Results from a prospective observational cohort study

BACKGROUND

The clinical importance of morningness-eveningness, especially in mood disorders, is prevailing. The differential relation of chronotype with diagnoses of early-onset mood disorders, mood symptoms, anxiety, and quality of life was evaluated.

METHODS

Early-onset mood disorder patients [n = 419; 146 major depressive disorder (MDD); 123 bipolar I disorder (BDI); 150 bipolar II disorder (BDII)] from the Mood Disorder Cohort Research Consortium were assessed for chronotype using the composite scale for morningness (CSM) and its association with clinical variables obtained during the clinician-verified euthymic state.

RESULTS

The mean total CSM of BDI was significantly higher than MDD and BDII (p < 0.001). In all types of mood disorders, higher total CSM was associated with lower Quick inventory of depressive symptomatology (p < 0.005) and higher WHO quality of life (p < 0.005). Such negative correlations between the total CSM and Montgomery-Asberg depression rating were significant in MDD and BDI (p < 0.05) and marginally significant in BDII (p = 0.077). CSM was a significant contributor to quality of life in BDI (p < 0.001) and BDII (p = 0.011), but it was not for MDD.

LIMITATIONS

The defined 'euthymic state' that may not fully reflect the remission of episode; limited generalizability due to clinical characteristic of early-onset mood disorder; the disparity between diurnal preference measured by the CSM and chronotype; possible effects of the last mood episode polarity and medication; and, lack of control group.

CONCLUSION

Less eveningness was associated with less severe depressive symptoms and better quality of life. This suggests that morningness may reduce residual depressive symptoms and recover function of patients.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.

Chronotype, circadian rhythm, and psychiatric disorders: Recent evidence and potential mechanisms

The circadian rhythm is crucial for physiological and behavioral functions. Chronotype, which represents individual preferences for activity and performance, is associated with human health issues, particularly psychiatric disorders. This narrative review, which focuses on the relationship between chronotype and mental disorders, provides an insight into the potential mechanism. Recent evidence indicates that (1) the evening chronotype is a risk factor for depressive disorders and substance use disorders, whereas the morning chronotype is a protective factor. (2) Evening chronotype individuals with bipolar disorder tend to have more severe symptoms and comorbidities. (3) The evening chronotype is only related to anxiety symptoms. (4) The relationship between chronotype and schizophrenia remains unclear, despite increasing evidence on their link. (5) The evening chronotype is significantly associated with eating disorders, with the majority of studies have focused on binge eating disorders. Furthermore, the underlying mechanisms or influence factors are described in detail, including clock genes, brain characteristics, neuroendocrinology, the light/dark cycle, social factors, psychological factors, and sleep disorders. These findings provide the latest evidence on chronotypes and psychiatric disorders and serve as a valuable reference for researchers.

Prior sleep-wake behaviors are associated with mental health outcomes during the COVID-19 pandemic among adult users of a wearable device in the United States

Objectives

To characterize objective sleep patterns among U.S. adults before and during the COVID-19 pandemic, and to assess for associations between adverse mental health symptoms and (1) sleep duration and (2) the consistency of sleep timing before and during the pandemic.

Design

Longitudinal objective sleep-wake data during January-June 2020 were linked with mental health and substance use assessments conducted during June 2020 for The COVID-19 Outbreak Public Evaluation (COPE) Initiative.

Setting

Adult users of WHOOP—a commercial, digital sleep wearable.

Participants

Adults residing in the U.S. and actively using WHOOP wearable devices, recruited by WHOOP, Inc.

Intervention

The COVID-19 pandemic and its mitigation.

Measurements

Anxiety or depression symptoms, burnout symptoms, and new or increased substance use to cope with stress or emotions.

Results

Of 4912 participants in the primary analytic sample (response rate, 14.9%), we observed acutely increased sleep duration (0.25 h or 15 m) and sleep consistency (3.51 points out of 100) and delayed sleep timing (onset, 18.7 m; offset, 36.6 m) during mid-March through mid-April 2020. Adjusting for demographic and lifestyle variables, participants with persistently insufficient sleep duration and inconsistent sleep timing had higher odds of adverse mental health symptoms and substance use in June 2020.

Conclusions

U.S. adult wearable users displayed increased sleep duration, more consistent sleep timing, and delayed sleep onset and offset times after the COVID-19 pandemic onset, with subsample heterogeneity. Associations between adverse mental health symptoms and pre- and mid-pandemic short sleep duration and inconsistent sleep timing suggest that these characteristics warrant further investigation as potential modifiable mental health and substance use risk factors.

Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort

PURPOSE

Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents overall sleep traits.

PATIENTS AND METHODS

We conducted a genome-wide association study (GWAS) of sleep health score (overall assessment of sleep duration, snoring, insomnia, chronotype, and daytime dozing) using 336,463 participants from the UK Biobank. Proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) were then performed to identify candidate genes at the protein and mRNA level, respectively. We finally used linkage disequilibrium score regression (LDSC) to estimate the genetic correlations between sleep health score and other functionally relevance traits.

RESULTS

GWAS identified multiple variants near known candidate genes associated with sleep health score, such as MEIS1, FBXL13, MED20 and SMAD5. HDHD2 (PPWAS = 0.0146) and GFAP (PPWAS = 0.0236) were identified associated with sleep health score by PWAS. TWAS identified ORC4 (PTWAS = 0.0212) and ZNF732 (PTWAS = 0.0349) considering mRNA expression level. LDSC found significant genetic correlations of sleep health score with 3 sleep behaviors (including insomnia, snoring, dozing), 4 psychiatry disorders (major depressive disorder, attention deficit/hyperactivity disorder, schizophrenia, autism spectrum disorder), and 9 plasma protein (such as Stabilin-1, Stromelysin-2, Cytochrome c) (all LDSC PLDSC < 0.05).

CONCLUSION

Our results advance the comprehensive understanding of the aetiology and genetic architecture of the sleep health score, refine the understanding of the relationship of sleep health score with other traits and diseases, and may serve as potential targets for future mechanistic studies of sleep phenotype.

Circadian disruption and human health

Circadian disruption is pervasive and can occur at multiple organizational levels, contributing to poor health outcomes at individual and population levels. Evidence points to a bidirectional relationship, in that circadian disruption increases disease severity and many diseases can disrupt circadian rhythms. Importantly, circadian disruption can increase the risk for the expression and development of neurologic, psychiatric, cardiometabolic, and immune disorders. Thus, harnessing the rich findings from preclinical and translational research in circadian biology to enhance health via circadian-based approaches represents a unique opportunity for personalized/precision medicine and overall societal well-being. In this Review, we discuss the implications of circadian disruption for human health using a bench-to-bedside approach. Evidence from preclinical and translational science is applied to a clinical and population-based approach. Given the broad implications of circadian regulation for human health, this Review focuses its discussion on selected examples in neurologic, psychiatric, metabolic, cardiovascular, allergic, and immunologic disorders that highlight the interrelatedness between circadian disruption and human disease and the potential of circadian-based interventions, such as bright light therapy and exogenous melatonin, as well as chronotherapy to improve and/or modify disease outcomes.