Potential mechanisms of traditional Chinese medicine in treating insomnia: A network pharmacology, GEO validation, and molecular-docking study.

The purpose of this study is to investigate the potential mechanisms of Chinese herbs for the treatment of insomnia using a combination of data mining, network pharmacology, and molecular-docking validation. All the prescriptions for insomnia treated by the academician Qi Wang from 2020 to 2022 were collected. The Ancient and Modern Medical Case Cloud Platform v2.3 was used to identify high-frequency Chinese medicinal herbs and the core prescription. The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were utilized to predict the effective active components and targets of the core herbs. Insomnia-related targets were collected from 4 databases. The intersecting targets were utilized to build a protein-protein interaction network and conduct gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the STRING database, Cytoscape software, and clusterProfiler package. Gene chip data (GSE208668) were obtained from the Gene Expression Omnibus database. The limma package was applied to identify differentially expressed genes (DEGs) between insomnia patients and healthy controls. To create a "transcription factor (TF)-miRNA-mRNA" network, the differentially expressed miRNAs were entered into the TransmiR, FunRich, Targetscan, and miRDB databases. Subsequently, the overlapping targets were validated using the DEGs, and further validations were conducted through molecular docking and molecular dynamics simulations. Among the 117 prescriptions, 65 herbs and a core prescription were identified. Network pharmacology and bioinformatics analysis revealed that active components such as ß-sitosterol, stigmasterol, and canadine acted on hub targets, including interleukin-6, caspase-3, and hypoxia-inducible factor-1α. In GSE208668, 6417 DEGs and 7 differentially expressed miRNAs were identified. A "TF-miRNA-mRNA" network was constructed by 4 "TF-miRNA" interaction pairs and 66 "miRNA-mRNA" interaction pairs. Downstream mRNAs exert therapeutic effects on insomnia by regulating circadian rhythm. Molecular-docking analyses demonstrated good docking between core components and hub targets. Molecular dynamics simulation displayed the strong stability of the complex formed by small molecule and target. The core prescription by the academician Qi Wang for treating insomnia, which involves multiple components, targets, and pathways, showed the potential to improve sleep, providing a basis for clinical treatment of insomnia.

Genetic correlation and causal associations between psychiatric disorders and lung cancer risk.

BACKGROUND: Patients with certain psychiatric disorders have increased lung cancer incidence. However, establishing a causal relationship through traditional epidemiological methods poses challenges. METHODS: Available summary statistics of genome-wide association studies of cigarette smoking, lung cancer, and eight psychiatric disorders, including attention deficit/hyperactivity disorder (ADHD), autism, depression, major depressive disorder, bipolar disorder, insomnia, neuroticism, and schizophrenia (range N: 46,350-1,331,010) were leveraged to estimate genetic correlations using Linkage Disequilibrium Score Regression and assess causal effect of each psychiatric disorder on lung cancer using two-sample Mendelian randomization (MR) models, comprising inverse-variance weighted (IVW), weighted median, MR-Egger, pleiotropy residual sum and outlier testing (MR-PRESSO), and a constrained maximum likelihood approach (cML-MR). RESULTS: Significant positive correlations were observed between each psychiatric disorder and both smoking and lung cancer (all FDR < 0.05), except for the correlation between autism and lung cancer. Both univariable and the cML-MA MR analyses demonstrated that liability to schizophrenia, depression, ADHD, or insomnia was associated with an increased risk of overall lung cancer. Genetic liability to insomnia was linked specifically to squamous cell carcinoma (SCC), while genetic liability to ADHD was associated with an elevated risk of both SCC and small cell lung cancer (all P < 0.05). The later was further supported by multivariable MR analyses, which accounted for smoking. LIMITATIONS: Participants were constrained to European ancestry populations. Causal estimates from binary psychiatric disorders may be biased. CONCLUSION: Our findings suggest appropriate management of several psychiatric disorders, particularly ADHD, may potentially reduce the risk of developing lung cancer.

Mendelian randomization study supports positive bidirectional causal relationships between genetically predicted insomnia symptom and liability to benign prostatic hyperplasia.

BACKGROUND: Sleep quality may be related to benign prostatic hyperplasia (BPH), however causal associations have not been established. This study aimed to evaluate causal relationships between six sleep traits ([i] day time napping, [ii] daytime sleepiness, [iii] insomnia, [iv] long sleep duration, [v] short sleep duration, and [vi] sleep duration per hour) and BPH through a bidirectional Mendelian randomization (MR) study. METHODS: Genome-wide association summary statistics of sleep traits and BPH were downloaded from public databases. Inverse variance weighting (IVW) was used as the main approach for causal inference. For causal estimates identified by IVW, various sensitivity analyses were performed to assess the reliability of the results: (i) four additional MR methods to complement IVW; (ii) Cochran's Q test to assess heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test to assess horizontal pleiotropy; and (iv) leave-one-out method to assess stability. RESULTS: Forward MR analyses indicated that genetically predicted insomnia symptom significantly increased BPH risk (OR = 1.267, 95% CI: 1.003-1.601, P = 0.048), while reverse MR analyses identified that genetically predicted liability to BPH significantly increased the incidence of insomnia (OR = 1.026, 95% CI: 1.000-1.052, P = 0.048). In a replicate MR analysis based on summary statistics including exclusively male participants, the finding of increased risk of BPH due to genetically predicted insomnia symptom was further validated (OR = 1.488, 95% CI: 1.096-2.022, P = 0.011). No further causal links were identified. In addition, sensitivity tests demonstrated the reliability of the MR results. CONCLUSION: This study identified that a higher prevalence of genetically predicted insomnia symptoms may significantly increase the risk of BPH, while genetically predicted liability to BPH may in turn increase the incidence of insomnia symptom. Therefore, improving sleep quality and reducing the risk of insomnia could be a crucial approach for the prevention of BPH.

Oculomasticatory rhythmic movements, insomnia and stroke-like episodes in a patient with POLG mutation.

The POLG mutation, a leading cause of mitochondrial diseases, exhibits a wide-ranging age of onset and a complex clinical presentation. We encountered an atypical clinical profile in an elderly man with a POLG mutation, characterised by a stroke-like episode, chronic insomnia and transient oculomasticatory rhythmic movement. History revealed chronic constipation since his 50s and progressive bilateral ophthalmoplegia since his early 60s. Subsequently, he had experienced acute encephalopathy and later developed chronic insomnia. The present neurological examination showed bilateral complete ophthalmoplegia, ptosis, and rhythmic ocular and jaw movements. Imaging indicated findings suggestive of a stroke-like episode and eventual genetic analysis revealed a homozygous missense mutation in the POLG gene. This case expands the clinical spectrum of POLG mutations in individuals over 60 years, showcasing the rare combination of a stroke-like episode, chronic insomnia and oculomasticatory rhythmic movement.

Causal relationship between the gut microbiota and insomnia: a two-sample Mendelian randomization study.

Background: Changes in the gut microbiota are closely related to insomnia, but the causal relationship between them is not yet clear. Objective: To clarify the relationship between the gut microbiota and insomnia and provide genetic evidence for them, we conducted a two-sample Mendelian randomization study. Methods: We used a Mendelian randomized two-way validation method to discuss the causal relationship. First, we downloaded the data of 462,341 participants relating to insomnia, and the data of 18,340 participants relating to the gut microbiota from a genome-wide association study (GWAS). Then, we used two regression models, inverse-variance weighted (IVW) and MR-Egger regression, to evaluate the relationship between exposure factors and outcomes. Finally, we took a reverse MR analysis to assess the possibility of reverse causality. Results: The combined results show 19 gut microbiotas to have a causal relationship with insomnia (odds ratio (OR): 1.03; 95% confidence interval (CI): 1.01, 1.05; p=0.000 for class. Negativicutes; OR: 1.03; 95% CI: 1.01, 1.05; p=0.000 for order.Selenomonadales; OR: 1.01; 95% CI: 1.00, 1.02; p=0.003 for genus.RikenellaceaeRC9gutgroup). The results were consistent with sensitivity analyses for these bacterial traits. In reverse MR analysis, we found no statistical difference between insomnia and these gut microbiotas. Conclusion: This study can provide a new direction for the causal relationship between the gut microbiota (class.Negativicutes, order.Selenomonadales, genus.Lactococcus) and insomnia and the treatment or prevention strategies of insomnia.

No evidence linking sleep traits with white blood cell counts: Multivariable-adjusted and Mendelian randomization analyses.

BACKGROUND: Disturbances in habitual sleep have been associated with multiple age-associated diseases. However, the biological mechanisms underpinning these associations remain largely unclear. We assessed the possible involvement of the circulating immune system by determining the associations between sleep traits and white blood cell counts using multivariable-adjusted linear regression and Mendelian randomization. METHODS: Cross-sectional multivariable-adjusted linear regression analyses were done using participants within the normal range of total white blood cell counts (>4.5 × 109 and <11.0 × 109/µL) from UK Biobank. For the sleep traits, we examined (short and long) sleep duration, chronotype, insomnia symptoms and daytime dozing. Two-sample Mendelian randomization analyses were done using instruments for sleep traits derived from European-ancestry participants from UK Biobank (over 410,000 participants) and using SNP-outcome data derived from European-ancestry participants from the Blood Cell Consortium (N = 563,946) to which no data from UK Biobank contributed. RESULTS: Using data from 357,656 participants (mean [standard deviation] age: 56.5 [8.1] years, and 44.4% men), we did not find evidence that disturbances in any of the studied sleep traits were associated with differences in blood cell counts (total, lymphocytes, neutrophiles, eosinophiles and basophiles). Also, we did not find associations between disturbances in any of the studied sleep traits and white blood cell counts using Mendelian Randomization. CONCLUSION: Based on the results from two different methodologies, disturbances in habitual sleep are unlikely to cause changes in blood cell counts and thereby differences in blood cell counts are unlikely to be underlying the observed sleep-disease associations.

Shared genetic architecture and causal relationship between sleep behaviors and lifespan.

Poor sleep health is associated with a wide array of increased risk for cardiovascular, metabolic and mental health problems as well as all-cause mortality in observational studies, suggesting potential links between sleep health and lifespan. However, it has yet to be determined whether sleep health is genetically or/and causally associated with lifespan. In this study, we firstly studied the genome-wide genetic association between four sleep behaviors (short sleep duration, long sleep duration, insomnia, and sleep chronotype) and lifespan using GWAS summary statistics, and both sleep duration time and insomnia were negatively correlated with lifespan. Then, two-sample Mendelian randomization (MR) and multivariable MR analyses were applied to explore the causal effects between sleep behaviors and lifespan. We found that genetically predicted short sleep duration was causally and negatively associated with lifespan in univariable and multivariable MR analyses, and this effect was partially mediated by coronary artery disease (CAD), type 2 diabetes (T2D) and depression. In contrast, we found that insomnia had no causal effects on lifespan. Our results further confirmed the negative effects of short sleep duration on lifespan and suggested that extension of sleep may benefit the physical health of individuals with sleep loss. Further attention should be given to such public health issues.

Nightmares share genetic risk factors with sleep and psychiatric traits.

Nightmares are vivid, extended, and emotionally negative or negative dreams that awaken the dreamer. While sporadic nightmares and bad dreams are common and generally harmless, frequent nightmares often reflect underlying pathologies of emotional regulation. Indeed, insomnia, depression, anxiety, or alcohol use have been associated with nightmares in epidemiological and clinical studies. However, the connection between nightmares and their comorbidities are poorly understood. Our goal was to examine the genetic risk factors for nightmares and estimate correlation or causality between nightmares and comorbidities. We performed a genome-wide association study (GWAS) in 45,255 individuals using a questionnaire-based assessment on the frequency of nightmares during the past month and genome-wide genotyping data. While the GWAS did not reveal individual risk variants, heritability was estimated at 5%. In addition, the genetic correlation analysis showed a robust correlation (rg > 0.4) of nightmares with anxiety (rg = 0.671, p = 7.507e-06), depressive (rg = 0.562, p = 1.282e-07) and posttraumatic stress disorders (rg = 0.4083, p = 0.0152), and personality trait neuroticism (rg = 0.667, p = 4.516e-07). Furthermore, Mendelian randomization suggested causality from insomnia to nightmares (beta = 0.027, p = 0.0002). Our findings suggest that nightmares share genetic background with psychiatric traits and that insomnia may increase an individual's liability to experience frequent nightmares. Given the significant correlations with psychiatric and psychological traits, it is essential to grow awareness of how nightmares affect health and disease and systematically collect information about nightmares, especially from clinical samples and larger cohorts.

Impact of insomnia upon inflammatory digestive diseases and biomarkers: a two-sample mendelian randomization research on Europeans.

BACKGROUND: A number of observational studies indicate that insomnia is linked to inflammatory digestive diseases (IDDs). However, the definite relationship between insomnia and IDDs remains unclear. METHODS: We obtained the publicly available data from genome-wide association studies (GWAS) to conduct two-sample Mendelian randomization (MR) for association assessment. Five MR analysis methods were used to calculate the odds ratio (OR) and effect estimate, and the heterogeneity and pleiotropy tests were performed to evaluate the robustness of the variable instruments (IVs). RESULTS: One exposure and twenty outcome datasets based on European populations were included in this study. Using the inverse variance weighted method, we found insomnia was closely correlated with esophageal ulcer (OR = 1.011, 95%CI = 1.004-1.017, p = 0.001) and abdominal pain (effect estimate = 1.016, 95%CI = 1.005-1.026, p = 0.003). Suggestive evidence of a positively association was observed between insomnia and duodenal ulcer (OR = 1.006, 95%CI = 1.002-1.011, p = 0.009), gastric ulcer (OR = 1.008, 95%CI = 1.001-1.014, p = 0.013), rectal polyp (OR = 1.005, 95%CI = 1.000-1.010, p = 0.034), haemorrhoidal disease (OR = 1.242, 95%CI = 1.004-1.535, p = 0.045) and monocyte percentage (effect estimate = 1.151, 95%CI = 1.028-1.288, p = 0.014). No correlations were observed among other IDDs, phenotypes and biomarkers. CONCLUSIONS: Our MR study assessed the relationship between insomnia and IDDs/phenotypes/biomarkers in depth and revealed potential associations between insomnia and ulcers of the esophagus and abdominal pain.

[Association between insomnia and type 2 diabetes: A two-sample Mendelian rando-mization study].

OBJECTIVE: To explore the robust relationship between insomnia and type 2 diabetes mellitus by two-sample Mendelian randomization analysis to overcome confounding factors and reverse causality in observational studies. METHODS: We identified strong, independent single nucleotide polymorphisms (SNPs) of insomnia from the most up to date genome wide association studies (GWAS) within European ancestors and applied them as instrumental variable to GWAS of type 2 diabetes mellitus. After excluding SNPs that were significantly associated with smoking, physical activity, alcohol consumption, educational attainment, obesity, or type 2 diabetes mellitus, we assessed the impact of insomnia on type 2 diabetes mellitus using inverse variance weighting (IVW) method. Weighted median and MR-Egger regression analysis were also conducted to test the robustness of the association. We calculated the F statistic of the selected SNPs to test the applicability of instrumental variable and F statistic over than ten indicated that there was little possibility of bias of weak instrumental variables. We further examined the existence of pleiotropy by testing whether the intercept term in MR-Egger regression was significantly different from zero. In addition, the leave-one-out method was used for sensitivity analysis to verify the stability and reliability of the results. RESULTS: We selected 248 SNPs independently associated with insomnia at the genome-wide level (P<5×10-8) as a preliminary candidate set of instrumental variables. After clumping based on the reference panel from 1000 Genome Project and removing the potential pleiotropic SNPs, a total of 167 SNPs associated with insomnia were included as final instrumental variables. The F statistic of this study was 39. 74, which was in line with the relevance assumption of Mendelian randomization. IVW method showed insomnia was associated with higher risk of type 2 diabetes mellitus that po-pulation with insomnia were 1. 14 times more likely to develop type 2 diabetes mellitus than those without insomnia (95% CI: 1.09-1.21, P<0.001). The weighted median estimator (WME) method and MR-Egger regression showed similar causal effect of insomnia on type 2 diabetes mellitus. And MR-Egger regression also showed that the effect was less likely to be triggered by pleiotropy. Sensitivity analyses produced directionally similar estimates. CONCLUSION: Insomnia is a risk factor of type 2 diabetes mellitus, which has positively effects on type 2 diabetes mellitus. Our study provides further rationale for indivi-duals at risk for diabetes to keep healthy lifestyle.

Causal association between sleep traits and autoimmune arthritis: Evidence from a bidirectional Mendelian randomization study.

OBJECTIVE: To explore whether there is a genetic causal relationship between sleep traits and the risk of autoimmune arthritis (AA). METHODS: Univariable and multivariable Mendelian randomization was employed using genome-wide association studies data to assess sleep traits' associations with AAs, including rheumatoid arthritis (RA), ankylosing spondylitis, and psoriatic arthritis. The inverse-variance weighted method served as the primary analysis, supplemented by the CAUSE method to improve power and mitigate false positives. Mediation Mendelian randomization was used to quantify direct and indirect effects. RESULTS: Significant associations were shown between insomnia symptoms and increased risk of overall RA (odds ratio = 2.75, 95% confidence interval 1.45-5.22) and seronegative RA (odds ratio = 6.95, 95% confidence interval 2.47-19.56). CAUSE results revealed an association of insomnia symptoms with overall RA and seronegative RA, as well as the sleep duration with overall RA. After the adjustment for body mass index, alcohol status, smoking status, and physical activity levels, multivariable analyses revealed that genetic predisposition to insomnia symptoms and prolonged sleep duration showed independent negative associations with the risk of overall RA and seropositive RA. In the reversed multivariable analyses, a borderline negative association was shown in the overall RA-sleep duration and a positive association of seropositive RA with the risk of insomnia symptoms. CONCLUSION: This study demonstrated a potential bidirectional causal relationship that genetic predisposition to insomnia symptoms and shorter sleep duration was associated with the risk of AA, especially RA. Genetic predisposition to RA was also associated with decreased sleep duration, as well as increased insomnia symptom risk.

Associations between sleep-behavioral traits and healthspan: A one-sample Mendelian randomization study based on 388,909 participants of the UK-Biobank.

BACKGROUND: Although the association between sleep behavior and morbidity and mortality risk has been reported before, there is still uncertainty whether the observed associations are causal or confounding. Therefore, we investigated the causal relationships between sleep-behavioral traits and terminated healthspan risk using Mendelian randomization (MR). METHODS: We conducted a one-sample MR analysis to evaluate causality between six sleep-behavioral traits (sleep duration, chronotype/morningness, napping, sleeplessness/insomnia, and getting up from bed) and risk of healthspan termination among 388, 909 UK Biobank (UKB) participants. Instrumental variables for sleep behaviors (N = 590) were obtained from recent genome-wide association studies (GWAS). We defined healthspan based on eight predominant health-terminating events associated with longevity (congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, diabetes, cancer, and death). We further constructed a sleep score and a weighted genetic risk score to increase the predictive ability of the sleep-behavioral traits. Cox regression models and Inverse Probability Treatment Weighting (IPTW) were implemented, followed by MR to assess causation. We used inverse-variance-weighted MR to estimate causal effects, and weighted-median and MR-egger for sensitivity analysis to test the pleiotropic effects. RESULTS: In IPTW, we observed a decreased risk of terminated healthspan for healthy sleep behaviors such as 'sleep duration 7-8h/d' (Hazard ratio, HR = 0.93; 95 % confidence interval, CI: 0.92-0.96; P < 0.001); 'morningness' (HR = 0.95; 95%CI: 0.93-0.98; P < 0.01); 'napping' (HR = 0.93; 95%CI: 0.91-0.94; P < 0.001); 'easy getting up from bed' (HR = 0.91; 95%CI: 0.88-0.93; P < 0.001); and, 'never/rarely experience sleeplessness/insomnia' (HR = 0.94; 95%CI: 0.92-0.96; P < 0.001). MR results further indicated causal associations between healthy sleep duration (OR = 0.98; 95%CI: 0.97-1.00; P = 0.036) and insomnia (OR = 1.02; 95%CI: 1.01-1.03; P < 0.001) with terminated healthspan. MR-egger did not suggest any potential pleiotropy. CONCLUSION: This study supports abnormal sleep duration and insomnia as potential causal risk factors for terminated healthspan. Thus, healthy sleep behavior is valuable for the extension of healthspan, and well-designed and tailored sleep health interventions are warranted.

Associations Between Sleep Traits and Social Isolation: Observational and Bidirectional Mendelian Randomization Study.

Social isolation has been found associated with multiple sleep traits in conventional observational studies. However, whether this association is causal and if so, its direction is uncertain. We analyzed the association between social isolation and multiple sleep traits in 30 430 participants from the Guangzhou Biobank Cohort Study. In bidirectional Mendelian randomization, we used 6, 17, and 11 single nucleotide polymorphisms associated with attendance at sports club/gym, religious group, and pub/social club from the UK Biobank (n = 452 302), respectively, and 152 single nucleotide polymorphisms associated with insomnia from the combination of UK Biobank and 23andme (n = 1 331 010). Observationally in the Guangzhou Biobank Cohort Study, insomnia (yes/no) (beta = 0.12, 95% confidence interval (CI) 0.10-0.16) and poor sleep quality (yes/no) (beta = 0.12, CI: 0.08-0.15), but not sleep duration and chronotype, were associated with a higher social isolation score (severe social isolation). In bidirectional MR, genetically predicted insomnia decreases the odds of attendance at sports club/gym (beta = 0.98, CI: 0.98-0.99) and religious groups (beta = 0.99, CI: 0.98-0.99), but not pub/social club. However, these 3 types of social activity were not associated with insomnia. Our results support the causal effects of insomnia on social activity. Further clinical investigations into the utility of insomnia treatment in alleviating social isolation are needed.

The interaction between polygenic risk and environmental influences: A direct test of the 3P model of insomnia in adolescents.

BACKGROUND: Stress is a universal phenomenon and one of the most common precipitants of insomnia. However, not everyone develops insomnia after experiencing a stressful life event. This study aims to test aspects of Spielman's '3P model of insomnia' (during adolescence) by exploring the extent to which: (a) insomnia symptoms are predicted by polygenic scores (PGS); (b) life events predict insomnia symptoms; (c) the interaction between PGS and life events contribute to the prediction of insomnia symptoms; (d) gene-environment interaction effects remain after controlling for sex. METHODS: The sample comprised 4,629 twins aged 16 from the Twin Early Development Study who reported on their insomnia symptoms and life events. PGS for insomnia were calculated. In order to test the main hypothesis of this study (a significant interaction between PGS and negative life events), we fitted a series of mixed effect regressions. RESULTS: The best fit was provided by the model including sex, PGS for insomnia, negative life events, and their interactions (AIC = 26,158.7). Our results show that the association between insomnia symptoms and negative life events is stronger for those with a higher genetic risk for insomnia. CONCLUSIONS: This work sheds light on the complex relationship between genetic and environmental factors implicated for insomnia. This study has tested for the first time the interaction between genetic predisposition (PGS) for insomnia and environmental stressors (negative life events) in adolescents. This work represents a direct test of components of Spielman's 3P model for insomnia which is supported by our results.

Heritability and genetic correlations for sleep apnea, insomnia, and hypersomnia in a large clinical biobank.

RATIONALE: Comorbid insomnia and sleep apnea is reported to have worse outcomes than either condition alone. The local genetic correlations of these disorders are unknown. OBJECTIVES: To identify local genomic regions with heritability for clinically diagnosed sleep apnea and insomnia, and to identify local genetic correlations between these disorders and/or hypersomnia. METHODS: Fifty thousand two hundred seventeen patients of European ancestry were examined. Global and local heritability and genetic correlations for independent regions were calculated, adjusting for obesity and other covariates. RESULTS: Sleep apnea and insomnia were significantly globally heritable and had 118 and 168 genetic regions with local heritability p-values <.05, respectively. One region had a significant genetic correlation for sleep apnea and hypersomnia (p-value = 9.85 × 10-4). CONCLUSIONS: Clinically diagnosed sleep apnea and insomnia have minimal shared genetic architecture, supporting genetically distinct comorbid insomnia and sleep apnea components. However, additional correlated regions may be identified with additional sample size and methodological improvements.

Multivariate genome-wide association study of sleep health demonstrates unity and diversity.

There has been a recent push to focus sleep research less on disordered sleep and more on the dimensional sleep health. Sleep health incorporates several dimensions of sleep: chronotype, efficiency, daytime alertness, duration, regularity, and satisfaction with sleep. A previous study demonstrated sleep health domains correlate only moderately with each other at the genomic level (|rGs| = 0.11-0.51) and show unique relationships with psychiatric domains (controlling for shared variances, duration, alertness, and non-insomnia independently related to a factor for internalizing psychopathology). Of the domains assessed, circadian preference was the least genetically correlated with all other facets of sleep health. This pattern is important because it suggests sleep health should be considered a multifaceted construct rather than a unitary construct. Prior genome-wide association studies (GWASs) have vastly increased our knowledge of the biological underpinnings of specific sleep traits but have only focused on univariate analyses. We present the first multivariate GWAS of sleep and circadian health (multivariate circadian preference, efficiency, and alertness factors, and three single-indicator factors of insomnia, duration, and regularity) using genomic structural equation modeling. We replicated loci found in prior sleep GWASs, but also discovered "novel" loci for each factor and found little evidence for genomic heterogeneity. While we saw overlapping genomic enrichment in subcortical brain regions and shared associations with external traits, much of the genetic architecture (loci, mapped genes, and enriched pathways) was diverse among sleep domains. These results confirm sleep health as a family of correlated but genetically distinct domains, which has important health implications.

The relationship between gut microbiota and insomnia: a bi-directional two-sample Mendelian randomization research.

Introduction: Insomnia is the second most common mental health issue, also is a social and financial burden. Insomnia affects the balance between sleep, the immune system, and the central nervous system, which may raise the risk of different systemic disorders. The gut microbiota, referred to as the "second genome," has the ability to control host homeostasis. It has been discovered that disruption of the gut-brain axis is linked to insomnia. Methods: In this study, we conducted MR analysis between large-scale GWAS data of GMs and insomnia to uncover potential associations. Results: Ten GM taxa were detected to have causal associations with insomnia. Among them, class Negativicutes, genus Clostridiuminnocuumgroup, genus Dorea, genus Lachnoclostridium, genus Prevotella7, and order Selenomonadalesare were linked to a higher risk of insomnia. In reverse MR analysis, we discovered a causal link between insomnia and six other GM taxa. Conclusion: It suggested that the relationship between insomnia and intestinal flora was convoluted. Our findings may offer beneficial biomarkers for disease development and prospective candidate treatment targets for insomnia.

Genetic study of the causal effect of lipid profiles on insomnia risk: a Mendelian randomization trial.

OBJECTIVES: In response to the controversy surrounding observational studies of the association between lipid profiles and the risk of insomnia, the aim of this study was to analyze lipid profiles, including triglycerides (TG), apolipoprotein A-1 (ApoA-1), apolipoprotein B (ApoB) and lipoprotein A (LPA), in a European population to further assess the causal relationship between these lipid types and insomnia. MATERIALS AND METHODS: This study explores the causal effect of lipid profiles on insomnia based on a genome-wide association study (GWAS)-derived public dataset using two-sample and multivariate Mendelian randomization (MVMR) analysis. The main MR analyses used inverse variance weighting (IVW) odds ratio (OR), and the sensitivity analyses included weighted median (WM) and MR‒Egger. RESULTS: Both MR and MVMR showed that lowering ApoA-1 and LPA levels had causal effects on the risk of insomnia [MR: per 10 units, ApoA-1: OR: 0.7546, 95% CI: 0.6075-0.9372, P = 0.011; LPA: OR: 0.8392, 95% CI: 0.7202-0.9778, P = 0.025; MVMR: per 10 units, ApoA-1: OR: 0.7600, 95% CI: 0.6362-0.9079, P = 0.002; LPA, OR: 0.903, 95% CI: 0.8283-0.9845, P = 0.021]. There were no causal effects of TG or ApoB on insomnia (all P > 0.05). The MR‒Egger intercept test, funnel plot, and IVW methods all suggested an absence of strong directional pleiotropy, and leave-one-out permutation analysis did not detect any single single-nucleotide polymorphism that had a strong influence on the results. CONCLUSION: Elevated levels of ApoA-1 and LPA were independently and causally associated with the risk of insomnia, suggesting that elevated ApoA-1 and LPA levels may contribute to a reduced risk of insomnia.

Causal relationship between sleep traits and cognitive impairment: A Mendelian randomization study.

OBJECTIVE: Observational studies had demonstrated a link between sleep disturbances and cognitive decline. Here, we aimed to investigate the causal association between genetically predicted sleep traits and cognitive impairment using Mendelian randomization (MR). METHODS: Using strict criteria, we selected genetic variants from European ancestry Genome-wide association studies (GWAS) from the Sleep Disorders Knowledge Portal and UK Biobank as instrumental variables for several sleep traits, including insomnia, sleep duration, daytime sleepiness, daytime napping, and chronotype. Summary statistics related to cognitive impairment were derived from five different GWAS, including the Social Science Genetic Association Consortium. The role of self-reported sleep trait phenotypes in the etiology of cognitive impairment was explored using inverse-variance weighted (IVW) tests, MR-Egger tests, and weighted medians, and sensitivity analyses were conducted to ensure robustness. RESULTS: In the main IVW analysis, sleep duration (reaction time: ß = -0.05, 95% CI -0.07 to -0.04, p = 1.93×10-12 ), daytime sleepiness (average cortical thickness: ß = -0.12, 95% CI -0.22 to -0.02, p = 0.023), and daytime napping (fluid intelligence: ß = -0.47, 95% CI -0.87 to -0.07, p = 0.021; hippocampal volume in Alzheimer's disease: ß = -0.99, 95% CI -1.64 to -0.35, p = 0.002) were significantly negatively correlated with cognitive performance. However, any effects of insomnia and chronotype on cognitive impairment were not determined. CONCLUSIONS: Our findings highlighted that focusing on sleep behaviors or distinct sleep patterns-particularly sleep duration, daytime sleepiness, and daytime napping, was a promising approach for preventing cognitive impairment. This study also shed light on risk factors for and potential early markers of cognitive impairment risk factors.

Dopamine multilocus genetic profile influence on reward network in chronic insomnia disorder with depression.

BACKGROUND: Chronic insomnia disorder (CID) is frequently comorbid with depression, and both conditions are believed to involve disruptions in the reward network. However, the potential effects of genetic polymorphisms in modulating this network remain largely unexplored. METHODS: In this study, we recruited 50 CID patients with high (CID-HD) and low (CID-LD) depressive symptoms and assessed their reward networks using resting-state functional MRI. Additionally, we calculated the multilocus genetic profile score (MGPS) to examine the influence of depression and dopamine genetic variation on the nucleus accumbens functional connectivity (NAFC) network in CID patients. RESULTS: Although the MGPS did not show a significant difference between the two CID groups, its influence on the NAFC network was observed in the salience network (SN) and visual network (VN) in CID patients. When comparing CID-HD patients to CID-LD patients, we found that CID-HD patients exhibited decreased NAFC in the internal reward network, default mode network, SN, and sensorimotor network, while showing increased NAFC in the executive control network (ECN) and VN. Furthermore, the influence of MGPS on the reward network was only significant in CID-HD patients, specifically in the internal reward network and ECN. CONCLUSION: These findings suggest that genetic variations related to dopamine may modulate the reward network differently in CID patients with and without depressive symptoms. These results contribute to our understanding of the pathophysiology of polygenic effects underlying brain network abnormalities in CID patients with depression.