Genome-wide analysis of insomnia disorder

Association of sleep quality and its change with the risk of depression in middle-aged and elderly people: A 10-year cohort study from England

BACKGROUND

Persistently poor sleep quality in young adults is linked to a higher risk of depression. However, the impact of changes in sleep quality on depression risk in middle-aged and older adults remain unclear. This study investigates the association between sleep quality, its changes, and the risk of depression in middle-aged and elderly people.

METHODS

We included 4007 participants (mean age 63.0 ± 7.6 years, 53.0 % women) from the English Longitudinal Study of Ageing. Sleep quality was assessed using the Jenkins Sleep Problems Scale and a global sleep quality question. Depression was evaluated with the Center for Epidemiological Studies Depression Scale and self-reported doctor-diagnosed depression. Multivariable logistic regression, restricted cubic spline curve, and mediation analysis was employed.

RESULTS

After 10 years of follow-up, 777 individuals developed depression. Sleep quality scores positively correlated with depression risk. Among those with good sleep quality, worsening sleep quality increased depression risk (OR = 1.67, 95 % CI: 1.21-2.31). For those with intermediate sleep quality, improved sleep quality reduced depression risk (OR = 0.70, 95 % CI: 0.50-0.98). Conversely, worsening sleep quality increased depression risk (OR = 2.11, 95 % CI: 1.47-3.02). Pain and functional disability partially mediated the association between intermediate/poor sleep quality and depression (9.8 % and 4.2 %, respectively).

LIMITATIONS

Sleep quality is based on self-reported.

CONCLUSIONS

Intermediate, poor, and worsening sleep quality are linked to higher depression risk. Improving sleep quality mitigates depression risk in those with intermediate sleep quality. Sleep quality may influence depression indirectly through pain and functional disability.

Bidirectional relationship between sleep and depression

Patients with depression almost inevitably exhibit abnormalities in sleep, such as shortened latency to enter rapid eye movement (REM) sleep and decrease in electroencephalogram delta power during non-REM sleep. Insufficient sleep can be stressful, and the accumulation of stress leads to the deterioration of mental health and contributes to the development of psychiatric disorders. Thus, it is likely that depression and sleep are bidirectionally related, i.e. development of depression contributes to sleep disturbances and vice versa. However, the relation between depression and sleep seems complicated. For example, acute sleep deprivation can paradoxically improve depressive symptoms. Thus, it is difficult to conclude whether sleep has beneficial or harmful effects in patients with depression. How antidepressants affect sleep in patients with depression might provide clues to understanding the effects of sleep, but caution is required considering that antidepressants have diverse effects other than sleep. Recent animal studies support the bidirectional relation between depression and sleep, and animal models of depression are expected to be beneficial for the identification of neuronal circuits that connect stress, sleep, and depression. This review provides a comprehensive overview regarding the current knowledge of the relationship between depression and sleep.

Periostracum Cicadae Extract and N-Acetyldopamine Regulate the Sleep-Related Neurotransmitters in PCPA-Induced Insomnia Rats

Insomnia is the second most prevalent mental illness worldwide. Periostracum cicadae (PC), as an animal traditional Chinese medicine with rich pharmacological effects, has been documented as a treatment for children's night cries, and later extended to treat insomnia. This study aimed to investigate the effects of PC extract and N-acetyldopamine compounds in ameliorating insomnia. The UPLC-ESI-QTOF-MS analysis determined that PC extract mainly contained N-acetyldopamine components. Previously, we also isolated some acetyldopamine polymers from PC extract, among which acetyldopamine dimer A (NADA) was present in high content. Molecular docking and molecular dynamic simulations demonstrated that NADA could form stable complexes with 5-HT1A, BDNF, and D2R proteins, respectively. The effects of PC extract and NADA on insomnia were evaluated in the PCPA-induced insomnia model. The results indicated that PC extract and NADA could effectively ameliorate hypothalamic pathology of insomnia rats, increase the levels of 5-HT, GABA, and BDNF, and decrease the levels of DA, DOPAC, and HVA. Meanwhile, the PC extract and NADA also could significantly affect the expression of 5-HT1A, BDNF, and DARPP-32 proteins. This study proved that PC extract and acetyldopamine dimer A could effectively improve PCPA-induced insomnia in rats. It is speculated that the main pharmacological substances of PC were acetyldopamine components.

Uncommon Protein-Coding Variants Associated With Suicide Attempt in a Diverse Sample of U.S. Army Soldiers

BACKGROUND

Suicide is a societal and public health concern of global scale. Identifying genetic risk factors for suicide attempt can characterize underlying biology and enable early interventions to prevent deaths. Recent studies have described common genetic variants for suicide-related behaviors. Here, we advance this search for genetic risk by analyzing the association between suicide attempt and uncommon variation exome-wide in a large, ancestrally diverse sample.

METHODS

We sequenced whole genomes of 13,584 soldiers from the Army STARRS (Army Study to Assess Risk and Resilience in Servicemembers), including 979 individuals with a history of suicide attempt. Uncommon, nonsilent protein-coding variants were analyzed exome-wide for association with suicide attempt using gene-collapsed and single-variant analyses.

RESULTS

We identified 19 genes with variants enriched in individuals with history of suicide attempt, either through gene-collapsed or single-variant analysis (Bonferroni padjusted < .05). These genes were CIB2, MLF1, HERC1, YWHAE, RCN2, VWA5B1, ATAD3A, NACA, EP400, ZNF585A, LYST, RC3H2, PSD3, STARD9, SGMS1, ACTR6, RGS7BP, DIRAS2, and KRTAP10-1. Most genes had variants across multiple genomic ancestry groups. Seventeen of these genes were expressed in healthy brain tissue, with 9 genes expressed at the highest levels in the brain versus other tissues. Brains from individuals deceased from suicide aberrantly expressed RGS7BP (padjusted = .035) in addition to nominally significant genes including YWHAE and ACTR6, all of which have reported associations with other mental disorders.

CONCLUSIONS

These results advance the molecular characterization of suicide attempt behavior and support the utility of whole-genome sequencing for complementing the findings of genome-wide association studies in suicide research.

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia

STUDY OBJECTIVES

The standard of care for military personnel with insomnia is cognitive behavioral therapy for insomnia (CBT-I). However, only a minority seeking insomnia treatment receive CBT-I, and little reliable guidance exists to identify those most likely to respond. As a step toward personalized care, we present results of a machine learning (ML) model to predict CBT-I response.

METHODS

Administrative data were examined for n = 1,449 nondeployed US Army soldiers treated for insomnia with CBT-I who had moderate-severe baseline Insomnia Severity Index (ISI) scores and completed 1 or more follow-up ISIs 6-12 weeks after baseline. An ensemble ML model was developed in a 70% training sample to predict clinically significant ISI improvement (reduction of at least 2 standard deviations on the baseline ISI distribution). Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample.

RESULTS

19.8% of patients had clinically significant ISI improvement. Model area under the receiver operating characteristic curve (standard error) was 0.60 (0.03). The 20% of test-sample patients with the highest probabilities of improvement were twice as likely to have clinically significant improvement compared with the remaining 80% (36.5% vs 15.7%; χ21 = 9.2, P = .002). Nearly 85% of prediction accuracy was due to 10 variables, the most important of which were baseline insomnia severity and baseline suicidal ideation.

CONCLUSIONS

Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment. Parallel models will be needed for alternative treatments before such a system is of optimal value.

CITATION

Gabbay FH, Wynn GH, Georg MW, et al. Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia. J Clin Sleep Med. 2024;20(6):921-931.

Clinical, genomic, and neurophysiological correlates of lifetime suicide attempts among individuals with an alcohol use disorder

Research has identified clinical, genomic, and neurophysiological markers associated with suicide attempts (SA) among individuals with psychiatric illness. However, there is limited research among those with an alcohol use disorder (AUD), despite their disproportionately higher rates of SA. We examined lifetime SA in 4,068 individuals with DSM-IV alcohol dependence from the Collaborative Study on the Genetics of Alcoholism (23% lifetime suicide attempt; 53% female; mean age: 38). Within participants with an AUD diagnosis, we explored risk across other clinical conditions, polygenic scores (PGS) for comorbid psychiatric problems, and neurocognitive functioning for lifetime suicide attempt. Participants with an AUD who had attempted suicide had greater rates of trauma exposure, major depressive disorder, post-traumatic stress disorder, and other substance use disorders compared to those who had not attempted suicide. Polygenic scores for suicide attempt, depression, and PTSD were associated with reporting a suicide attempt (ORs = 1.22 - 1.44). Participants who reported a SA also had decreased right hemispheric frontal-parietal theta and decreased interhemispheric temporal-parietal alpha electroencephalogram resting-state coherences relative to those who did not, but differences were small. Overall, individuals with an AUD who report a lifetime suicide attempt appear to experience greater levels of trauma, have more severe comorbidities, and carry polygenic risk for a variety of psychiatric problems. Our results demonstrate the need to further investigate suicide attempts in the presence of substance use disorders.

Investigating the Role of BDNF in Insomnia: Current Insights

Insomnia is a common disorder defined as frequent and persistent difficulty initiating, maintaining, or going back to sleep. A hallmark symptom of this condition is a sense of nonrestorative sleep. It is frequently associated with other psychiatric disorders, such as depression, as well as somatic ones, including immunomediated diseases. BDNF is a neurotrophin primarily responsible for synaptic plasticity and proper functioning of neurons. Due to its role in the central nervous system, it might be connected to insomnia of multiple levels, from predisposing traits (neuroticism, genetic/epigenetic factors, etc.) through its influence on different modes of neurotransmission (histaminergic and GABAergic in particular), maintenance of circadian rhythm, and sleep architecture, and changes occurring in the course of mood disturbances, substance abuse, or dementia. Extensive and interdisciplinary evaluation of the role of BDNF could aid in charting new areas for research and further elucidate the molecular background of sleep disorder. In this review, we summarize knowledge on the role of BDNF in insomnia with a focus on currently relevant studies and discuss their implications for future projects.

Potential genetic and epigenetic mechanisms in insomnia: A systematic review

Insomnia is a stress-related sleep disorder conceptualised within a diathesis-stress framework, which it is thought to result from predisposing factors interacting with precipitating stressful events that trigger the development of insomnia. Among predisposing factors genetics and epigenetics may play a role. A systematic review of the current evidence for the genetic and epigenetic basis of insomnia was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) system. A total of 24 studies were collected for twins and family heritability, 55 for genome-wide association studies, 26 about candidate genes for insomnia, and eight for epigenetics. Data showed that insomnia is a complex polygenic stress-related disorder, and it is likely to be caused by a synergy of genetic and environmental factors, with stress-related sleep reactivity being the important trait. Even if few studies have been conducted to date on insomnia, epigenetics may be the framework to understand long-lasting consequences of the interaction between genetic and environmental factors and effects of stress on the brain in insomnia. Interestingly, polygenic risk for insomnia has been causally linked to different mental and medical disorders. Probably, by treating insomnia it would be possible to intervene on the effect of stress on the brain and prevent some medical and mental conditions.

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 importance and limitations of polysomnography in insomnia disorder-a critical appraisal

The importance polysomnography (PSG) in the diagnosis and treatment process of insomnia disorder (ID) remains highly disputed. This review summarises the state of the science regarding PSG indications and findings in ID, and the indications to conduct PSG in ID as stated by relevant guidelines. It then highlights the most relevant questions regarding the topic, including the relevance of ID subtyping, to allow an individualised pharmacological or psychotherapeutic treatment approach.

Identification of six genes associated with COVID-19-related circadian rhythm dysfunction by integrated bioinformatic analysis

Patients with coronavirus disease 2019 (COVID-19) might cause long-term burden of insomnia, while the common pathogenic mechanisms are not elucidated. The gene expression profiles of COVID-19 patients and healthy controls were retrieved from the GEO database, while gene set related with circadian rhythm was obtained from GeneCards database. Seventy-six shared genes were screened and mainly enriched in cell cycle, cell division, and cell proliferation, and 6 hub genes were found out including CCNA2, CCNB1, CDK1, CHEK1, MKI67, and TOP2A, with positive correlation to plasma cells. In the TF-gene regulatory network, NFYA, NFIC, MEF2A, and FOXC1 showed high connectivity with hub genes. This study identified six hub genes and might provide new insights into pathogenic mechanisms and novel clinical management strategies.

Anxiety and Insomnia Mediate the Association of Fear of Infection and Fatigue: A Cross-Sectional Survey of Nurses Deployed to a COVID-19 Epicenter in China

Background

This study aimed to test the mediating role of anxiety and insomnia in the association between fear of infection and fatigue.

Methods

A cross-sectional questionnaire survey was conducted on the nurses deployed to Heihe. A serial multiple mediation model was established to determine the role of anxiety and insomnia in the association between fear of infection and fatigue.

Findings

Over half (53.0%) of the study participants reported experiencing fear of infection despite stringent personal protection measures. The scores of anxiety (11.87±5.19), insomnia (16.33±5.95), and fatigue (45.94±12.93) were moderately correlated, with a Pearson correlation coefficient ranging from 0.501 to 0.579. Anxiety, either alone or in combination with insomnia, mediated the association between fear of infection and fatigue.

Conclusion

The findings suggest that anxiety and insomnia play a mediating role in the relationship between fear of infection and fatigue. These results emphasize the importance of implementing targeted mental health interventions and work arrangements to address the well-being of healthcare professionals.

Toward personalized care for insomnia in the US Army: development of a machine-learning model to predict response to pharmacotherapy

STUDY OBJECTIVES

Although many military personnel with insomnia are treated with prescription medication, little reliable guidance exists to identify patients most likely to respond. As a first step toward personalized care for insomnia, we present results of a machine-learning model to predict response to insomnia medication.

METHODS

The sample comprised n = 4,738 nondeployed US Army soldiers treated with insomnia medication and followed 6-12 weeks after initiating treatment. All patients had moderate-severe baseline scores on the Insomnia Severity Index (ISI) and completed 1 or more follow-up ISIs 6-12 weeks after baseline. An ensemble machine-learning model was developed in a 70% training sample to predict clinically significant ISI improvement, defined as reduction of at least 2 standard deviations on the baseline ISI distribution. Predictors included a wide range of military administrative and baseline clinical variables. Model accuracy was evaluated in the remaining 30% test sample.

RESULTS

21.3% of patients had clinically significant ISI improvement. Model test sample area under the receiver operating characteristic curve (standard error) was 0.63 (0.02). Among the 30% of patients with the highest predicted probabilities of improvement, 32.5.% had clinically significant symptom improvement vs 16.6% in the 70% sample predicted to be least likely to improve (χ21 = 37.1, P < .001). More than 75% of prediction accuracy was due to 10 variables, the most important of which was baseline insomnia severity.

CONCLUSIONS

Pending replication, the model could be used as part of a patient-centered decision-making process for insomnia treatment, but parallel models will be needed for alternative treatments before such a system is of optimal value.

CITATION

Gabbay FH, Wynn GH, Georg MW, et al. Toward personalized care for insomnia in the US Army: development of a machine-learning model to predict response to pharmacotherapy. J Clin Sleep Med. 2023;19(8):1399-1410.

Sleep disturbances and depression are bidirectionally associated among college student athletes across COVID-19 pandemic exposure classes

College athletes may be vulnerable to sleep disturbances and depression during the COVID-19 pandemic as a result of large shifts in social and athletic obligations. In a national sample of college athletes, we examined the associations between sleep disturbances and depression across two timepoints, using COVID-19 exposure as a moderator. Data were collected from 2098 NCAA Division I, II, and III college athletes during two timepoints, from April 10 to May 23, and from August 4 to September 15, 2020. First, a latent class analysis was conducted with five indicators of levels of COVID-19 exposure to determine different exposure profiles. Second, to examine the directionality of associations between sleep disturbance and depression, a cross-lagged panel model was added to the latent class membership structural equation model; this allowed for testing of moderation by COVID exposure class membership. Four highly homogeneous, well-separated classes of COVID-19 exposure were enumerated: Low Exposure (57%); Quarantine Only (21%); High Other, Low Self Exposure (14%); and High Exposure (8%). COVID-19 exposure class membership did not significantly moderate associations between sleep disturbances and depression. However, student athletes significantly differed in T2 depression by their COVID-19 exposure class membership. Depression and sleep disturbances were positively correlated at both timepoints (r T1 = 0.39; r T2 = 0.30). Additionally, cross-lagged associations were found such that T2 depression was associated with T1 sleep disturbances (β = 0.14) and vice versa (β = 0.11). These cross-lagged associations were not significantly affected by athletes' level of COVID-19 exposure during the beginning of the pandemic.

Association of changes in sleep duration and quality with incidence of depression: A cohort study

BACKGROUND

The longitudinal relationship between sleep duration, sleep quality, and their changes with the risk of depressive symptoms is unclear. We examined the association between sleep duration, sleep quality, and their changes with incident depressive symptoms.

METHODS

A total of 225,915 Korean adults without depression at baseline with a mean age of 38.5 years were followed for an average of 4.0 years. Sleep duration and quality were assessed using the Pittsburgh Sleep Quality Index. The presence of depressive symptoms was assessed using the Center for Epidemiologic Studies Depression scale. Flexible parametric proportional hazard models were used to determine hazard ratios (HRs) and 95 % confidence intervals (CIs).

RESULTS

In total, 30,104 participants with incident depressive symptoms were identified. Multivariable-adjusted HRs (95 % CIs) for incident depression comparing sleep durations of ≤5, 6, 8, and ≥9 h with 7 h were 1.15 (1.11-1.20), 1.06 (1.03-1.09), 0.99 (0.95-1.03), and 1.06 (0.98-1.14), respectively. A similar trend was observed in patients with poor sleep quality. Compared with participants with persistently good sleep quality, participants with persistently poor sleep quality or who developed poor sleep quality were associated with the risk of incident depressive symptoms [HRs (95 % CIs) of 2.13 (2.01-2.25) and 1.67 (1.58-1.77), respectively].

LIMITATIONS

Sleep duration was assessed using self-reported questionnaire and the study population may not reflect general population.

CONCLUSIONS

Sleep duration, sleep quality and their changes were independently associated with incident depressive symptoms in young adults, suggesting that inadequate sleep quantity and quality play a role in depression risk.

Relationship between antenatal sleep quality and depression in perinatal women: A comprehensive meta-analysis of observational studies

BACKGROUND

Perinatal depression is a global mental health problem. Studies have suggested that perinatal depression is related to poor sleep quality during pregnancy. However, evidence on the influence and mechanism of sleep quality on the risk of developing perinatal depression remains limited and inconclusive.

METHODS

A systematic review was conducted in PubMed, Web of Science, Embase, CINAHI and Cochrane Library for relevant original quantitative studies published in English. A hand search of the reference list of relevant studies was also performed. Meta-analysis was performed using RevMan software and a random-effects model. Potential heterogeneity source was explored by subgroup and sensitivity analyses, and potential publication bias was tested using funnel plots and Begg's test.

RESULTS

A total of ten studies involving 39,574 participants were included in our meta-analysis. Overall, women who experienced poor sleep quality during pregnancy were at a significantly higher risk of developing depression, with antenatal depression 3.72 times higher, postpartum depression 2.71 times higher, and perinatal depression 3.46 times higher, compared to those did not experience poor sleep quality.

LIMITATIONS

Different measuring tools and unobserved confounding factors may make some bias in our result. What's more, not all included studies were initially designed to assess the association between antenatal sleep quality and the risk of developing perinatal depression.

CONCLUSION

Our meta-analysis found that antenatal sleep quality was negatively associated with the risk for perinatal depression. Our findings highlight the importance of improving sleep quality during pregnancy for mental health among perinatal women.

Treatment of insomnia based on the mechanism of pathophysiology by acupuncture combined with herbal medicine: A review

Insomnia is a sleep disorder which severely affects patients mood, quality of life and social functioning, serves as a trigger or risk factor to a variety of diseases such as depression, cardiovascular and cerebrovascular diseases, obesity and diabetes, and even increases the risk of suicide, and has become an increasingly widespread concern worldwide. Considerable research on insomnia has been conducted in modern medicine in recent years and encouraging results have been achieved in the fields of genetics and neurobiology. Unfortunately, however, the pathogenesis of insomnia remains elusive to modern medicine, and pharmacological treatment of insomnia has been regarded as conventional. However, in the course of treatment, pharmacological treatment itself is increasingly being questioned due to potential dependence and drug resistance and is now being replaced by cognitive behavior therapy as the first-line treatment. As an important component of complementary and alternative medicine, traditional Chinese medicine, especially non-pharmacological treatment methods such as acupuncture, is gaining increasing attention worldwide. In this article, we discuss the combination of traditional Chinese medicine, acupuncture, and medicine to treat insomnia based on neurobiology in the context of modern medicine.

Pre-deployment threat learning predicts increased risk for post-deployment insomnia: Evidence from the Marine Resiliency Study

Insomnia is a common and impairing consequence of military deployment, but little is known about pre-deployment risk factors for post-deployment insomnia. Abnormal threat learning tendencies are commonly observed in individuals with insomnia and maladaptive responses to stress have been implicated in the development of insomnia, suggesting that threat learning could be an important risk factor for post-deployment insomnia. Here, we examined pre-deployment threat learning as a predictor of post-deployment insomnia and the potential mechanisms underlying this effect. Male servicemembers (N = 814) completed measures of insomnia, psychiatric symptoms, and a threat learning task before and after military deployment. Threat learning indices that differentiated participants with versus withoutinsomnia at post-deployment were tested as pre-deployment predictors of post-deployment insomnia. Post-deployment insomnia was linked to elevations on several threat learning indices at post-deployment, but only higher threat conditioning, as indexed by higher threat expectancy ratings to the danger cue, emerged as a pre-deployment predictor of post-deployment insomnia. This effect was independent of combat exposure levels and partially mediated by greater post-deployment nightmares. The tendency to acquire stronger expectations of aversive events following encounters with danger cues may increase risk for post-deployment insomnia, in part due to the development of more severe nightmares.

Association between telomere length and insomnia: A mendelian randomization and colocalization study

BACKGROUND

Previous studies have suggested a potential association between sleep and telomere length (TL), but its genetic basis remains unclear. In this study, we aimed to explore the genetic correlation and potential causal association between TL and insomnia.

METHODS

The genome-wide association study (GWAS) datasets of TL and insomnia-related traits were used, including insomnia, snoring, daytime dozing and napping. Based on the polygenic risk scores (PRS) of TL, linear regression and linkage disequilibrium score (LDSC) regression were used to preliminarily explore the association between TL and insomnia parameters in the UK Biobank cohort. Then, we investigated the causal association between TL and insomnia by mendelian randomization (MR) analysis and colocalization analysis.

RESULTS

In the UK Biobank cohort, the association between TL and insomnia was observed in the female samples (t = 2.968, P = 3.00 × 10^-3). LDSC detected a genetic correlation between short TL and insomnia (Rg = -9.27 × 10^-2, P = 8.00 × 10^-4). We found no evidence supporting significant causal association between insomnia and TL in IVW method (b = -5.95 × 10^-3, P = 0.57), with horizontal pleiotropy and heterogeneity tests indicating the validity of our MR study. Finally, rs12638862 was classified as colocalized by COLOC (PP4 = 0.99), and TERC may be involved in regulating the association between insomnia and TL.

CONCLUSIONS

Our study found no evidence for causal association between insomnia and TL in individuals of European ancestry. We detected a candidate gene associated with both insomnia and TL, providing novel clues for understanding the roles of this association.

Evaluation of potentially inappropriate medications in older patients admitted to the cardiac intensive care unit according to the 2019 Beers criteria, STOPP criteria version 2 and Chinese criteria

WHAT IS KNOWN AND OBJECTIVES

Potential inappropriate medications (PIMs) can increase the risk of medication-induced harm. However, there are no studies regarding PIMs in older and critically ill patients with cardiovascular diseases in China. Therefore, studies evaluating PIMs in these patients can help in the implementation of more effective interventions to reduce the risk of drug use. Our objective was to analyse the prevalence of PIMs in elderly patients admitted to the cardiac intensive care unit (CICU) comparing the 2019 Beers criteria (Beers criteria), Screening Tool of Older People's Potentially Inappropriate Prescriptions (STOPP) criteria version 2 (STOPP criteria) and criteria of potentially inappropriate medications for older adults in China (Chinese criteria); and analyse the factors influencing the PIMs.

METHODS

This cross-sectional and retrospective study was performed with elderly patients (≥65 years) admitted to the CICU of the Beijing Tongren Hospital in China from January 2019 to June 2020. The PIMs were identified based on the Chinese, STOPP and Beers criteria at admission and discharge. The three criteria were compared using the Kappa statistic. Multiple regression analysis was used to investigate the influencing factors associated with PIMs.

RESULTS AND DISCUSSION

A total of 369 patients who met the inclusion/exclusion criteria were included in this study. According to the three criteria used to evaluate the PIMs, the prevalence was 78.3% and 72.6% at admission and discharge, respectively. The prevalence rate of PIMs determined by the Chinese criteria was 62.1% at admission versus 56.6% at discharge (p = 0.134); the Beers criteria was 53.9% at admission versus 46.9% at discharge (p = 0.056); by the STOPP criteria was 20.6% at admission versus 13.8% at discharge (p = 0.015). Moreover, 28.9% (STOPP criteria), 56.8% (Beers criteria) and 73.4% (Chinese criteria) of patients taking PIMs on admission still had the same problem at discharge. The most common PIMs screened by the Beers, STOPP and Chinese criteria were diuretics, benzodiazepines and clopidogrel, respectively. Besides, the three criteria showed poor agreement. Finally, the stronger predictor of PIMs was the increased number of medications (p < 0.05).

WHAT IS NEW AND CONCLUSION

The prevalence of PIMs in elderly patients admitted to the CICU was high. The Chinese, STOPP and Beers criteria are effective screening tools to detect PIMs, but the consistency between them was poor. The increased number of medications was a significant predictor of PIMs.

Physical inactivity amplifies the negative association between sleep quality and depressive symptoms

Poor sleep quality and physical inactivity are known risk factors for depressive symptoms. Yet, whether these factors differently contribute to depressive symptoms and whether they interact with one another remains unclear. Here, we examined how sleep quality and physical activity influence depressive symptoms in 79,274 adults 50 years of age or older (52.4% women) from the Survey of Health, Aging and Retirement in Europe (SHARE) study. Sleep quality (poor vs. good), physical activity (inactive vs. active), and depressive symptoms (0 to 12 score) were repeatedly collected (7 waves of data collection) between 2004 and 2017. Results showed that sleep quality and physical activity were associated with depressive symptoms. Specifically, participants with poorer sleep quality reported more depressive symptoms than participants with better sleep quality (b = 1.85, 95% CI = 1.83-1.86, p < .001). Likewise, compared to physically active participants, physically inactive participants reported more depressive symptoms (b = 0.44, 95% CI = 0.42-0.45, p < .001). Moreover, sleep quality and physical activity showed an interactive association with depressive symptoms (b = 0.17, 95% CI = 0.13-0.20, p < .001). The negative association between poor sleep quality and higher depressive symptoms was stronger in physically inactive than active participants. These findings suggest that, in adults 50 years of age or older, both poor sleep quality and physical inactivity are related to an increase in depressive symptoms. Moreover, the detrimental association between poor sleep quality and depressive symptoms is amplified in physically inactive individuals.

Insomnia

Insomnia is highly prevalent in clinical practice, occurring in up to 50% of primary care patients. Insomnia can present independently or alongside other medical conditions or mental health disorders and is a risk factor for the development and exacerbation of these other disorders if not treated. In 2016, the American College of Physicians recommended that insomnia be specifically targeted for treatment. The recommended first-line treatment for insomnia, whether the underlying cause has been identified or not, is cognitive behavioural therapy for insomnia (CBT-I). Currently, there is no global consensus regarding which pharmacological treatment has the best efficacy or risk-benefit ratio. Both CBT-I and pharmacological intervention are thought to have similar acute effects, but only CBT-I has shown durable long-term effects after treatment discontinuation. Administering a combined treatment of CBT-I and medication could decrease the latency to treatment response, but might diminish the durability of the positive treatment effects of CBT-I.

Investigating the genetic pathways of insomnia in Autism Spectrum Disorder

BACKGROUND

Sleep problems are common in children with autism spectrum disorder (autism). There is sparse research to date to examine whether insomnia in people with autism is related to autism genetics or insomnia genetics. Moreover, there is a lack of research examining whether circadian-rhythm related genes share potential pathways with autism.

AIMS

To address this research gap, we tested whether polygenic scores of insomnia or autism are related to risk of insomnia in people with autism, and whether the circadian genes are associated with insomnia in people with autism.

METHODS AND PROCEDURES

We tested these questions using the phenotypically and genotypically rich MSSNG dataset (N = 1049) as well as incorporating in the analyses data from the Vanderbilt University Biobank (BioVU) (N = 349).

OUTCOMES AND RESULTS

In our meta-analyzed sample, there was no evidence of associations between the polygenic scores (PGS) for insomnia and a clinical diagnosis of insomnia, or between the PGS of autism and insomnia. We also did not find evidence of a greater burden of rare and disruptive variation in the melatonin and circadian genes in individuals with autism and insomnia compared to individuals with autism without insomnia.

CONCLUSIONS AND IMPLICATIONS

Overall, we did not find evidence for strong effects of genetic scores influencing sleep in people with autism, however, we cannot rule out the possibility that smaller genetic effects may play a role in sleep problems. Our study indicated the need for a larger collection of data on sleep problems and sleep quality among people with autism.

Daridorexant for the Treatment of Insomnia

Purpose of Review

Insomnia is a complex sleeping disorder that affects the lives of many individuals worldwide. Insomnia often occurs in the presence of coexisting comorbidities making it a complex disorder that requires a multifactorial approach to therapy. First-line therapy is cognitive-behavioral therapy for insomnia (CBT-I). Pharmacotherapy for insomnia falls into four classes based on mechanism of action: benzodiazepine receptor agonists (BZRAs), histamine receptor antagonists, melatonin receptor agonists, and dual orexin receptor antagonists (DORAs).

Recent Findings

Daridorexant is a dual orexin type 1 and types 2 (OX1 and OX2) receptor antagonist that was recently approved by the US FDA for the treatment of adults suffering from insomnia. It was shown to be effective in reducing insomnia symptoms, increasing daytime functioning, and improving the overall quality of sleep. Daridorexant offers patients relief from insomnia while avoiding the severe side effects and dependency issues of traditional treatments like benzodiazepines and sedatives.

Summary

In this article, we review the most recent data on insomnia treatments and summarize the safety and efficacy of daridorexant in treating insomnia.

Identification of Novel Genetic Variants Associated with Insomnia and Migraine Comorbidity

Purpose

Although insomnia and migraine are often comorbid, the genetic association between insomnia and migraine remains unclear. This study aimed to identify susceptibility loci associated with insomnia and migraine comorbidity.

Patients and Methods

We performed a genome-wide association study (GWAS) involving 1063 clinical outpatients at a tertiary hospital in Taiwan. Migraineurs with and without insomnia were genotyped using the Affymetrix Axiom Genome-Wide TWB 2.0. We performed association analyses for the entire cohort and stratified patients into the following subgroups: episodic migraine (EM), chronic migraine (CM), migraine with aura (MA), and migraine without aura (MoA). Potential correlations between SNPs and clinical indices in migraine patients with insomnia were examined using multivariate regression analysis.

Results

The SNP rs1178326 in the gene HDAC9 was significantly associated with insomnia. In the EM, CM, MA, and MoA subgroups, we identified 30 additional susceptibility loci. Multivariate regression analysis showed that SNP rs1178326 also correlated with higher migraine frequency and the Migraine Disability Assessment (MIDAS) questionnaire score. Finally, two SNPs that had been previously reported in a major insomnia GWAS were also significant in our migraineurs, showing a concordant effect.

Conclusion

In this GWAS, we identified several novel loci associated with insomnia in migraineurs in a Han Chinese population in Taiwan. These results provide insights into the possible genetic basis of insomnia and migraine comorbidity.

Towards organism-level systems biology by next-generation genetics and whole-organ cell profiling

The system-level identification and analysis of molecular and cellular networks in mammals can be accelerated by "next-generation" genetics, which is defined as genetics that can achieve desired genetic makeup in a single generation without any animal crossing. We recently established a highly efficient procedure for producing knock-out (KO) mice using the "Triple-CRISPR" method, which targets a single gene by triple gRNAs in the CRISPR/Cas9 system. This procedure achieved an almost perfect KO efficiency (96-100%). We also established a highly efficient procedure, the "ES-mouse" method, for producing knock-in (KI) mice within a single generation. In this method, ES cells were treated with three inhibitors to keep their potency and then injected into 8-cell-stage embryos. These procedures dramatically shortened the time required to produce KO or KI mice from years down to about 3 months. The produced KO and KI mice can also be systematically profiled at a single-cell resolution by the "whole-organ cell profiling," which was realized by tissue-clearing methods, such as CUBIC, and an advanced light-sheet microscopy. The review describes the establishment and application of these technologies above in analyzing the three states (NREM sleep, REM sleep, and awake) of mammalian brains. It also discusses the role of calcium and muscarinic receptors in these states as well as the current challenges and future opportunities in the next-generation mammalian genetics and whole-organ cell profiling for organism-level systems biology.

Prevalence of insomnia symptoms and associated risk factors in UK Biobank participants with hazardous alcohol use and major depression

INTRODUCTION

We aimed to examine the prevalence of insomnia symptoms (IS), sleep duration, and associated risk factors in participants with hazardous/harmful alcohol use (HAU), major depressive disorders (MDD), and HAU+MDD.

METHODS

Data from the UK Biobank (UKB) (n = 55,000) were utilized to categorize participants into those with MDD (n = 5612), HAU (n = 15,893), MDD+HAU (n = 3738), and controls (n = 29,511). We examined whether rates of IS and sleep duration differed among the groups and determined the clinical predictors of IS. Rates of IS and sleep duration were compared using regression analyses accounting for demographic (age, sex, ethnicity, Townsend deprivation index) and clinical (body mass index, neuroticism score, alcohol consumption) factors.

RESULTS

The unadjusted prevalence of IS was 26.5%, 27%, 39.5%, and 43% in control, HAU, MDD, and MDD+HAU categories respectively. Rates of IS in controls versus HAU and MDD versus MDD+HAU did not differ in unadjusted models (p = 0.45 and 0.075, respectively). Prevalence of IS differed in the four groups (p < 0.0001 for all pairwise comparisons) after adjusting for demographic confounders. After further adjustment for clinical factors, effect sizes were reduced, but pairwise comparisons remained significant. After adjusting for demographic and clinical factors, sleep duration did not differ among the groups. After accounting for diagnostic category and demographic/clinical factors, older age (OR=1.33 per 10 year increase; p < 0.0001), female sex (OR=1.39; p < 0.0001), obesity (OR=1.17 compared to normal; p < 0.0001), higher neuroticism score (OR=1.13; p < 0.0001), and alcohol consumption (OR=1.01 per serving increase; p < 0.0001) were associated with IS.

CONCLUSION

Sleep-related morbidity is the greatest in the MDD+HAU group, followed by the MDD group. Demographic and clinical characteristics explain some, but not all of the differences in the prevalence of IS in MDD±HAU. Genetic and other factors capable of influencing IS in those with MDD, HAU, and MDD+HAU merit future investigation.

GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia

Major depressive disorder (MDD) is one of the most prevalent and disabling mental disorders worldwide. Among the symptoms of MDD, sleep disturbance such as insomnia is prominent, and the first reason patients may seek professional help. However, the underlying pathophysiology of this comorbidity is still elusive. Recently, genome-wide association studies (GWAS) have begun to unveil the genetic background of several psychiatric disorders, including MDD and insomnia. Identifying the shared genomic risk loci between comorbid psychiatric disorders could be a valuable strategy to understanding their comorbidity. This study seeks to identify the shared genes and biological pathways between MDD and insomnia based on their shared genetic variants. First, we performed a meta-analysis based on the GWAS summary statistics of MDD and insomnia obtained from Psychiatric Genomics Consortium and UK Biobank, respectively. Next, we associated shared genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, a total of 719 shared genes were identified. Over half (51%) of them are protein-coding genes. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification, sensory perception, and immunologic signatures. We also identified druggable targets using a network approach. Together, these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid MDD and insomnia symptoms.

FAAH and CNR1 Polymorphisms in the Endocannabinoid System and Alcohol-Related Sleep Quality

Sleep disturbances are common among individuals with alcohol use disorder (AUD) and may not resolve completely with short-term abstinence from alcohol, potentially contributing to relapse to drinking. The endocannabinoid system (ECS) is associated with both sleep and alcohol consumption, and genetic variation in the ECS may underlie sleep-related phenotypes among individuals with AUD. In this study, we explored the influence of genetic variants in the ECS (Cannabinoid receptor 1/CNR1: rs806368, rs1049353, rs6454674, rs2180619, and Fatty Acid Amide Hydrolase/FAAH rs324420) on sleep quality in individuals with AUD (N = 497) and controls without AUD (N = 389). We assessed subjective sleep quality (from the Pittsburgh Sleep Quality Index/PSQI) for both groups at baseline and objective sleep efficiency and duration (using actigraphy) in a subset of individuals with AUD at baseline and after 4 weeks of inpatient treatment. We observed a dose-dependent relationship between alcohol consumption and sleep quality in both AUD and control groups. Sleep disturbance, a subscale measure in PSQI, differed significantly among CNR1 rs6454674 genotypes in both AUD (p = 0.015) and controls (p = 0.016). Only among controls, neuroticism personality scores mediated the relationship between genotype and sleep disturbance. Objective sleep measures (sleep efficiency, wake bouts and wake after sleep onset), differed significantly by CNR1 rs806368 genotype, both at baseline (p = 0.023, 0.029, 0.015, respectively) and at follow-up (p = 0.004, p = 0.006, p = 0.007, respectively), and by FAAH genotype for actigraphy recorded sleep duration at follow-up (p = 0.018). These relationships suggest a significant role of the ECS in alcohol-related sleep phenotypes.

Identifying novel genetic variants for brain amyloid deposition: a genome-wide association study in the Korean population

BACKGROUND

Genome-wide association studies (GWAS) have identified a number of genetic variants for Alzheimer's disease (AD). However, most GWAS were conducted in individuals of European ancestry, and non-European populations are still underrepresented in genetic discovery efforts. Here, we performed GWAS to identify single nucleotide polymorphisms (SNPs) associated with amyloid β (Aβ) positivity using a large sample of Korean population.

METHODS

One thousand four hundred seventy-four participants of Korean ancestry were recruited from multicenters in South Korea. Discovery dataset consisted of 1190 participants (383 with cognitively unimpaired [CU], 330 with amnestic mild cognitive impairment [aMCI], and 477 with AD dementia [ADD]) and replication dataset consisted of 284 participants (46 with CU, 167 with aMCI, and 71 with ADD). GWAS was conducted to identify SNPs associated with Aβ positivity (measured by amyloid positron emission tomography). Aβ prediction models were developed using the identified SNPs. Furthermore, bioinformatics analysis was conducted for the identified SNPs.

RESULTS

In addition to APOE, we identified nine SNPs on chromosome 7, which were associated with a decreased risk of Aβ positivity at a genome-wide suggestive level. Of these nine SNPs, four novel SNPs (rs73375428, rs2903923, rs3828947, and rs11983537) were associated with a decreased risk of Aβ positivity (p < 0.05) in the replication dataset. In a meta-analysis, two SNPs (rs7337542 and rs2903923) reached a genome-wide significant level (p < 5.0 × 10-8). Prediction performance for Aβ positivity increased when rs73375428 were incorporated (area under curve = 0.75; 95% CI = 0.74-0.76) in addition to clinical factors and APOE genotype. Cis-eQTL analysis demonstrated that the rs73375428 was associated with decreased expression levels of FGL2 in the brain.

CONCLUSION

The novel genetic variants associated with FGL2 decreased risk of Aβ positivity in the Korean population. This finding may provide a candidate therapeutic target for AD, highlighting the importance of genetic studies in diverse populations.

The role of sex chromosomes and sex hormones in vocal learning systems

Vocal learning is the ability to imitate and modify sounds through auditory experience, a rare trait found in only a few lineages of mammals and birds. It is a critical component of human spoken language, allowing us to verbally transmit speech repertoires and knowledge across generations. In many vocal learning species, the vocal learning trait is sexually dimorphic, where it is either limited to males or present in both sexes to different degrees. In humans, recent findings have revealed subtle sexual dimorphism in vocal learning/spoken language brain regions and some associated disorders. For songbirds, where the neural mechanisms of vocal learning have been well studied, vocal learning appears to have been present in both sexes at the origin of the lineage and was then independently lost in females of some subsequent lineages. This loss is associated with an interplay between sex chromosomes and sex steroid hormones. Even in species with little dimorphism, like humans, sex chromosomes and hormones still have some influence on learned vocalizations. Here we present a brief synthesis of these studies, in the context of sex determination broadly, and identify areas of needed investigation to further understand how sex chromosomes and sex steroid hormones help establish sexually dimorphic neural structures for vocal learning.

Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

Long-term changes in self-reported sleep quality and risk of chronic musculoskeletal pain: The HUNT Study

We examined the association between long-term (~10 years) changes in self-reported sleep quality and risk of any chronic musculoskeletal pain and chronic widespread pain. The study comprised data on 6,033 people who participated in three consecutive surveys in the Norwegian HUNT Study (1995-1997, 2006-2008 and 2017-2019) and who were without chronic musculoskeletal pain at the first two surveys. We used a modified Poisson regression model to calculate adjusted risk ratios for chronic pain at follow-up (2017-2019) associated with categories of poor and good sleep quality reported in 1995-1997 and 2006-2008. Compared with people who reported good sleep at both surveys (crude absolute risk: 32.4%), the risk ratios of any chronic pain were 1.20 (95% confidence interval: 1.02-1.41) for those who changed from poor to good sleep; 1.25 (95% confidence interval: 1.12-1.39) for those who changed from good to poor sleep; and 1.41 (95% confidence interval: 1.21-1.63) for those who reported long-term poor sleep. The corresponding risk ratios for chronic widespread pain were 1.35 (95% confidence interval: 0.82-2.23), 1.55 (95% confidence interval: 1.14-2.12) and 2.09 (95% confidence interval: 1.38-3.17), respectively. In conclusion, these findings indicate that people with long-term poor sleep quality have a markedly higher risk of chronic musculoskeletal pain and chronic widespread pain, compared with people who remain good sleep quality.

Molecular genetic overlap between posttraumatic stress disorder and sleep phenotypes

STUDY OBJECTIVES

Sleep problems are common, serving as both a predictor and symptom of posttraumatic stress disorder (PTSD), with these bidirectional relationships well established in the literature. While both sleep phenotypes and PTSD are moderately heritable, there has been a paucity of investigation into potential genetic overlap between sleep and PTSD. Here, we estimate genetic correlations between multiple sleep phenotypes (including insomnia symptoms, sleep duration, daytime sleepiness, and chronotype) and PTSD, using results from the largest genome-wide association study (GWAS) to date of PTSD, as well as publicly available GWAS results for sleep phenotypes within UK Biobank data (23 variations, encompassing four main phenotypes).

METHODS

Genetic correlations were estimated utilizing linkage disequilibrium score regression (LDSC), an approach that uses GWAS summary statistics to compute genetic correlations across traits, and Mendelian randomization (MR) analyses were conducted to follow up on significant correlations.

RESULTS

Significant, moderate genetic correlations were found between insomnia symptoms (rg range 0.36-0.49), oversleeping (rg range 0.32-0.44), undersleeping (rg range 0.48-0.49), and PTSD. In contrast, there were mixed results for continuous sleep duration and daytime sleepiness phenotypes, and chronotype was not correlated with PTSD. MR analyses did not provide evidence for casual effects of sleep phenotypes on PTSD.

CONCLUSION

Sleep phenotypes, particularly insomnia symptoms and extremes of sleep duration, have shared genetic etiology with PTSD, but causal relationships were not identified. This highlights the importance of further investigation into the overlapping influences on these phenotypes as sample sizes increase and new methods to investigate directionality and causality become available.

Integrative genomics analysis identifies five promising genes implicated in insomnia risk based on multiple omics datasets

In recent decades, many genome-wide association studies on insomnia have reported numerous genes harboring multiple risk variants. Nevertheless, the molecular functions of these risk variants conveying risk to insomnia are still ill-studied. In the present study, we integrated GWAS summary statistics (N=386,533) with two independent brain expression quantitative trait loci (eQTL) datasets (N=329) to determine whether expression-associated SNPs convey risk to insomnia. Furthermore, we applied numerous bioinformatics analyses to highlight promising genes associated with insomnia risk. By using Sherlock integrative analysis, we detected 449 significant insomnia-associated genes in the discovery stage. These identified genes were significantly overrepresented in six biological pathways including Huntington’s disease (P=5.58 × 10⁻⁵), Alzheimer’s disease (P=5.58 × 10⁻⁵), Parkinson’s disease (P=6.34 × 10⁻⁵), spliceosome (P=1.17 × 10⁻⁴), oxidative phosphorylation (P=1.09 × 10⁻⁴), and wnt signaling pathways (P=2.07 × 10⁻⁴). Further, five of these identified genes were replicated in an independent brain eQTL dataset. Through a PPI network analysis, we found that there existed highly functional interactions among these five identified genes. Three genes of LDHA (P=0.044), DALRD3 (P=5.0 × 10⁻⁵), and HEBP2 (P=0.032) showed significantly lower expression level in brain tissues of insomnic patients than that in controls. In addition, the expression levels of these five genes showed prominently dynamic changes across different time points between behavioral states of sleep and sleep deprivation in mice brain cortex. Together, the evidence of the present study strongly suggested that these five identified genes may represent candidate genes and contributed risk to the etiology of insomnia.

Multi-ethnic GWAS and meta-analysis of sleep quality identify MPP6 as a novel gene that functions in sleep center neurons

Poor sleep quality can have harmful health consequences. Although many aspects of sleep are heritable, the understandings of genetic factors involved in its physiology remain limited. Here, we performed a genome-wide association study (GWAS) using the Pittsburgh Sleep Quality Index (PSQI) in a multi-ethnic discovery cohort (n = 2868) and found two novel genome-wide loci on chromosomes 2 and 7 associated with global sleep quality. A meta-analysis in 12 independent cohorts (100 000 individuals) replicated the association on chromosome 7 between NPY and MPP6. While NPY is an important sleep gene, we tested for an independent functional role of MPP6. Expression data showed an association of this locus with both NPY and MPP6 mRNA levels in brain tissues. Moreover, knockdown of an orthologue of MPP6 in Drosophila melanogaster sleep center neurons resulted in decreased sleep duration. With convergent evidence, we describe a new locus impacting human variability in sleep quality through known NPY and novel MPP6 sleep genes.

Genetic versus stress and mood determinants of sleep in the Amish

Sleep is essential to the human brain and is regulated by genetics with many features conserved across species. Sleep is also influenced by health and environmental factors; identifying replicable genetic variants contributing to sleep may require accounting for these factors. We examined how stress and mood disorder contribute to sleep and impact its heritability. Our sample included 326 Amish/Mennonite individuals with a lifestyle with limited technological interferences with sleep. Sleep measures included Pittsburgh Sleep Quality Index (PSQI), bedtime, wake time, and time to sleep onset. Current stress level, cumulative life stressors, and mood disorder were also evaluated. We estimated the heritability of sleep features and examined the impact of current stress, lifetime stress, mood diagnosis on sleep quality. The results showed current stress, lifetime stress, and mood disorder were independently associated with PSQI score (p < .05). Heritability of PSQI was low (0-0.23) before and after accounting for stress and mood. Bedtime, wake time, and minutes to sleep time did show significant heritability at 0.44, 0.42, and 0.29. However, after adjusting for shared environment, only heritability of wake time remained significant. Sleep is affected by environmental stress and mental health factors even in a society with limited technological interference with sleep. Wake time may be a more biological marker of sleep as compared to the evening measures which are more influenced by other household members. Accounting for nongenetic and partially genetic determinants of sleep particularly stress and mood disorder is likely important for improving the precision of genetic studies of sleep.

Associations of sleep phenotypes with severe intentional self-harm: a prospective analysis of the UK Biobank cohort

STUDY OBJECTIVES

We aimed to investigate the prospective associations of sleep phenotypes with severe intentional self-harm (ISH) in middle-aged and older adults.

METHODS

A total of 499,159 participants (mean age: 56.55 ± 8.09 years; female: 54.4%) were recruited from the UK Biobank between 2006 and 2010 with follow-up until February 2016 in this population-based prospective study. Severe ISH was based on hospital inpatient records or a death cause of ICD-10 codes X60-X84. Patients with hospitalized diagnosis of severe ISH before the initial assessment were excluded. Sleep phenotypes, including sleep duration, chronotype, insomnia, sleepiness, and napping, were assessed at the initial assessments. Cox regression analysis was used to estimate temporal associations between sleep phenotypes and future risk of severe ISH.

RESULTS

During a follow-up period of 7.04 years (SD: 0.88), 1,219 participants experienced the first hospitalization or death related to severe ISH. After adjusting for demographics, substance use, medical diseases, mental disorders, and other sleep phenotypes, short sleep duration (HR: 1.50, 95% CI: 1.23-1.83, P < .001), long sleep duration (HR: 1.56, 95% CI: 1.15-2.12, P = .004), and insomnia (usually: HR: 1.57, 95% CI: 1.31-1.89, P < .001) were significantly associated with severe ISH. Sensitivity analyses excluding participants with mental disorders preceding severe ISH yielded similar results.

CONCLUSION

The current study provides the empirical evidence of the independent prediction of sleep phenotypes, mainly insomnia, short and long sleep duration, for the future risk of severe ISH among middle-aged and older adults.

DNA Methylation Biomarkers of IQ Reduction are Associated with Long-term Lead Exposure in School Aged Children in Southern China

Although lead associated with intelligence decline in children has long been reported, studies combining intelligence determination, molecular mechanisms exploration, and biomarker screen are quite rare. In this study, based on 333 children aged 9-11, we determined the role of DNA methylation (DNAm) in the relationship of lead exposure with children's intelligence. DNAm was measured from children's blood DNA specimens, and mediation analysis was performed to identify DNAm biomarkers mediating the lead-intelligence relationship. We identified forty-three differentially methylated regions (DMRs), and two fragments (FAM50B1 and PTCHD3) significantly mediated the lead-intelligence relationship, with contribution rates of 30.36% (p = 0.010) and 60.36% (p < 0.001), respectively. In addition, blood lead levels (BLLs) lower than 100 μg/L still adversely affected children's IQs and DNAm of the two fragments. Our data suggests that DNAm mediates lead-associated cognitive delay in children and blood lead reference value for school-aged children (100 μg/L) should be revised, and the candidate biomarkers can be used in related neurological diseases in future.

Development and Validation of Nomogram Prediction Model for Postoperative Sleep Disturbance in Patients Undergoing Non-Cardiac Surgery: A Prospective Cohort Study

PURPOSE

To develop a risk prediction nomogram of postoperative sleep disturbance (PSD) in patients undergoing non-cardiac surgery.

PATIENTS AND METHODS

Data on 881 consecutive patients who underwent non-cardiac surgery at the Affiliated Hospital of Xuzhou Medical University between June 2020 and April 2021 were prospectively collected. Of these, we randomly divided 881 non-cardiac patients into two groups, training cohort (n = 617) and validation cohort (n = 264) at the ratio of 7:3. Characteristic variables were selected based on the data of training cohort through least absolute shrinkage and selection operator (LASSO) regression. Multivariate logistic regression was used to identify the independent risk factors associated with PSD that then were incorporated into the nomogram. The predictive performance of the nomogram was measured by concordance index (C index), receiver operating characteristic (ROC) curve, and calibration with 1000 bootstrap samples to decrease the over-fit bias.

RESULTS

PSD was found in 443 of 617 patients (71.8%) and 190 of 264 patients (72.0%) in the training and validation cohorts, respectively. The perioperative risk factors associated with PSD were female sex, anxiety, dissatisfaction of ward environment, absence of combined regional nerve block, postoperative nausea and vomiting (PONV), the longer duration stayed in post anesthesia care unit (PACU), the higher dose of midazolam and sufentanil, the higher postoperative numeric rating score for pain (NRS) score. Incorporating these 9 factors, the nomogram achieved good concordance indexes of 0.82 (95% confidence interval [CI], 0.78-0.85) and 0.80 (95% CI, 0.74-0.85) in predicting PSD in the training and validation cohorts, respectively, and obtained well-fitted calibration curves. The sensitivity and specificity (95% CIs) of the nomogram were calculated, resulting in sensitivity of 74.0% (70.0-78.2%) and 75.3% (68.4-81.7%) and specificity of 79.3% (72.5-85.2%) and 70.3% (58.4-80.7%) for the training and validation cohorts, respectively. Patients who had a nomogram score of less than 262 or 262 or greater were considered to have low or high risks of PSD presence, respectively.

CONCLUSION

The proposed nomogram achieved an optimal prediction of PSD in patients undergoing non-cardiac surgery. The risks for an individual patient to harbor PSD can be determined by this model, which can lead to a reasonable preventive and treatment measures.

Introduction to the Clock System

Circadian (24-h) rhythms dictate almost everything we do, setting our clocks for specific times of sleeping and eating, as well as optimal times for many other basic functions. The physiological systems that coordinate circadian rhythms are intricate, but at their core, they all can be distilled down to cell-autonomous rhythms that are then synchronized within and among tissues. At first glance, these cell-autonomous rhythms may seem rather straight-forward, but years of research in the field has shown that they are strikingly complex, responding to many different external signals, often with remarkable tissue-specificity. To understand the cellular clock system, it is important to be familiar with the major players, which consist of pairs of proteins in a triad of transcriptional/translational feedback loops. In this chapter, we will go through each of the core protein pairs one-by-one, summarizing the literature as to their regulation and their broader impacts on circadian gene expression. We will conclude by briefly examining the human genetics literature, as well as providing perspectives on the future of the study of the molecular clock.

The Different Faces of Insomnia

Objectives: The identification of clinically relevant subtypes of insomnia is important. Including a comprehensive literature review, this study also introduces new phenotypical relevant parameters by describing a specific insomnia cohort. Methods: Patients visiting the sleep center and indicating self-reported signs of insomnia were examined by a sleep specialist who confirmed an insomnia diagnosis. A 14-item insomnia questionnaire on symptoms, progression, sleep history and treatment, was part of the clinical routine. Results: A cohort of 456 insomnia patients was described (56% women, mean age 52 ± 16 years). They had suffered from symptoms for about 12 ± 11 years before seeing a sleep specialist. About 40-50% mentioned a trigger (most frequently psychological triggers), a history of being bad sleepers to begin with, a family history of sleep problems, and a negative progression of insomnia. Over one third were not able to fall asleep during the day. SMI (sleep maintenance insomnia) symptoms were most frequent, but only prevalence of EMA (early morning awakening) symptoms significantly increased from 40 to 45% over time. Alternative non-medical treatments were effective in fewer than 10% of cases. Conclusion: Our specific cohort displayed a long history of suffering and the sleep specialist is usually not the first point of contact. We aimed to describe specific characteristics of insomnia with a simple questionnaire, containing questions (e.g., ability to fall asleep during the day, effects of non-medical therapy methods, symptom stability) not yet commonly asked and of unknown clinical relevance as yet. We suggest adding them to anamnesis to help differentiate the severity of insomnia and initiate further research, leading to a better understanding of the severity of insomnia and individualized therapy. This study is part of a specific Research Topic introduced by Frontiers on the heterogeneity of insomnia and its comorbidity and will hopefully inspire more research in this area.

The heritability of insomnia: A meta-analysis of twin studies

Twin studies of insomnia exhibit heterogeneity in estimates of heritability. This heterogeneity is likely because of sex differences, age of the sample, the reporter and the definition of insomnia. The aim of the present study was to systematically search the literature for twin studies investigating insomnia disorder and insomnia symptoms and to meta-analyse the estimates of heritability derived from these studies to generate an overall estimate of heritability. We further examined whether heritability was moderated by sex, age, reporter and insomnia symptom. A systematic literature search of five online databases was completed on 24 January 2020. Two authors independently screened 5644 abstracts, and 160 complete papers for the inclusion criteria of twin studies from the general population reporting heritability statistics on insomnia or insomnia symptoms, written in English, reporting data from independent studies. We ultimately included 12 papers in the meta-analysis. The meta-analysis focussed on twin intra-class correlations for monozygotic and dizygotic twins. Based on these intra-class correlations, the meta-analytic estimate of heritability was estimated at 40%. Moderator analyses showed stronger heritability in females than males; and for parent-reported insomnia symptoms compared with self-reported insomnia symptoms. There were no other significant moderator effects, although this is likely because of the small number of studies that were comparable across levels of the moderators. Our meta-analysis provides a robust estimate of the heritability of insomnia, which can inform future research aiming to uncover molecular genetic factors involved in insomnia vulnerability.

Gene polymorphisms (rs324957, rs324981) in NPSR1 are associated with increased risk of primary insomnia: A cross-sectional study

Neuropeptide S and neuropeptide S receptor (NPSR1) are associated with sleep regulation. Herein, the possible contribution of 6 polymorphisms in NPSR1 on the chromosome to primary insomnia (PI) and objective sleep phenotypes was investigated.The study included 157 patients with PI and 133 age- and sex-matched controls. All subjects were investigated by polysomnography for 3 consecutive nights. The genotyping of 6 polymorphisms was carried out by polymerase chain reaction-restriction fragment length polymorphism method.A significant difference was detected for rs324957 and rs324981 between PI and controls. The PI patients had a higher frequency of AA than controls in rs324957 (P = .02) and rs324981 (P = .04). However, for other single nucleotide polymorphisms (rs323922, rs324377, rs324396, and rs324987), no significant differences were observed between PI patients and controls. There were 2 different allelic combinations that were associated with PI susceptibility (CATGTC, GCCAAT) and its risk factor. A significant difference in sleep latency was observed among 3 genotype carriers of NPSR1 gene polymorphism rs324957 in PI group (P = .04), with carriers of the A/A genotype having the longest sleep latency (mean ± SD: 114.80 ± 58.27), followed by the A/G genotype (112.77 ± 46.54) and the G/G genotype (92.12 ± 42.72).This study provided the evidence that the NPSR1 gene polymorphisms (rs324957, rs324981) might be susceptibility loci for PI. Further studies are needed to explore the role of NPSR1 gene polymorphisms in molecular mechanisms of PI in a larger sample size.

Factors associated with insomnia among Chinese front-line nurses fighting against COVID-19 in Wuhan: A cross-sectional survey

Aim

To investigate the prevalence of insomnia among front‐line nurses fighting against COVID‐19 in Wuhan, China, and analyse its influencing factors.

Background

Insomnia is an important factor that can affect the health and work quality of nurses. However, there is a lack of big‐sample studies exploring factors that affect the insomnia of nurses fighting against COVID‐19.

Method

This cross‐sectional study using the Ascension Insomnia Scale, Fatigue Scale‐14 and Perceived Stress Scale took place in March 2020. Participants were 1,794 front‐line nurses from four tertiary‐level general hospitals.

Results

The prevalence of insomnia among participants was 52.8%. Insomnia was predicted by gender, working experience, chronic diseases, midday nap duration, direct participation in the rescue of patients with COVID‐19, frequency of night shifts, professional psychological assistance during the pandemic, negative experiences (such as family, friends or colleagues being seriously ill or dying due to COVID‐19), the degree of fear of COVID‐19, fatigue and perceived stress.

Conclusion

The level of insomnia among participants was higher than the normal level. Interventions based on influencing factors should be implemented to ensure nurses’ sleep quality.

Implications for Nursing Management

An in‐depth understanding of the influencing factors of insomnia among front‐line nurses can help nurse managers develop solutions to improve front‐line nurses’ sleep quality, which will enhance the physical and mental conditions of nurses and promote the quality of care.

Genome-wide association analysis of insomnia using data from Partners Biobank

Insomnia is one of the most prevalent and burdensome mental disorders worldwide, affecting between 10–20% of adults and up to 48% of the geriatric population. It is further associated with substance usage and dependence, as well other psychiatric disorders. In this study, we combined electronic health record (EHR) derived phenotypes and genotype information to conduct a genome wide analysis of insomnia in a 18,055 patient cohort. Diagnostic codes were used to identify 3,135 patients with insomnia. Our genome-wide association study (GWAS) identified one novel genomic risk locus on chromosome 8 (lead SNP rs17052966, p = 4.53 × 10⁻⁹, odds ratio = 1.28, se = 0.04). The heritability analysis indicated that common SNPs accounts for 7% (se = 0.02, p = 0.015) of phenotypic variation. We further conducted a large-scale meta-analysis of our results and summary statistics of two recent insomnia GWAS and 13 significant loci were identified. The genetic correlation analysis yielded a strong positive genetic correlation between insomnia and alcohol use (rG = 0.56, se = 0.14, p < 0.001), nicotine use (rG = 0.50, se = 0.12, p < 0.001) and opioid use (rG = 0.43, se = 0.18, p = 0.02) disorders, suggesting a significant common genetic risk factors between insomnia and substance use.