Mendelian randomization highlights sleep disturbances mediated the effect of depression on chronic pain.

INTRODUCTION: Depression and chronic pain are significant contributors to the global burden of disease. Previous research has revealed complex relationships between these two conditions, which may be influenced by sleep quality. However, observational studies have limitations, including confounding factors and reverse causation. This study aims to explore the mediating effects of sleep on the relationship between depression and chronic pain using Mendelian randomization (MR). METHODS: We conducted a two-step, two-sample MR study using mediation analysis. We obtained major depressive disorder (MDD) Genome-Wide Association Studdies (GWAS) data from Wray et al.'s GWAS meta-analysis. Phenotypic data related to sleep were collected from the UK Biobank. Chronic pain data were obtained from the Finnish database. RESULTS: MR analysis revealed significant genetic associations between MDD and chronic localized pain [IVW: odds ratio (OR) = 1.26, 95% confidence interval (CI) = 1.16-1.38, p = 2.52 × 10-7] as well as fibromyalgia (IVW: OR = 2.17, 95% CI = 1.34-3.52, p = .002). Genetic susceptibility for MDD was also associated with insomnia (IVW: OR = 1.10, 95% CI = 1.06-1.13, p = 3.57 × 10-8) and self-reported short sleep duration (IVW: OR = 1.03, 95% CI = 1.00-1.06, p = .047). The mediating effects of insomnia and fibromyalgia on the pathway from depression to chronic regional pain were 1.04 and 1.03, respectively, with mediation proportions of 12.8% and 15.2%. Insomnia mediated the pathway between depression and fibromyalgia with an effect of 1.12, accounting for 15.2% of the total effect. CONCLUSION: This two-step MR analysis strengthens the evidence of genetic predictive associations between depression and chronic pain, highlighting the mediating roles of insomnia and short sleep duration. It further elucidates the specific roles of distinct sleep disorders, differentiating insomnia and short sleep duration from other sleep-related phenotypes.

Causal relationship between sleep disorders and the risk of Alzheimer's disease: A Mendelian randomization study.

BACKGROUND AND OBJECTIVE: Epidemiological studies have shown that sleep disorders are risk factors for Alzheimer's disease (AD), but the causal relationship between sleep disorders and AD risk is unknown. We aim to assess the potential genetic causal association between sleep characteristics and AD, which may contribute to early identification and prediction of risk factors for AD. METHODS: Seven sleep-related traits and the outcome phenotype AD were selected from published genome-wide association studies (GWASs). These sleep-related characteristics and instrumental variables (IVs) for AD were extracted. Two-sample and multivariate Mendelian randomization (MR) analyses were performed to assess the causal relationships between sleep characteristics and AD. The inverse variance weighted (IVW), weighted median (WME), weighted mode (WM), MR-Egger regression (MR-Egger) and simple mode (SM) models were used to evaluate causality. The existence of pleiotropy was detected and corrected by MR-Egger regression, MR pleiotropy residuals and outliers. RESULTS: A two-sample MR study revealed a positive causal association between sleep duration and the onset of AD (OR = 1.002, 95 % CI: 1.000-1.004), and the risk of AD increased with increasing sleep duration. The MR-Egger regression method and MR-PRESSO were used to identify and correct pleiotropy, indicating that there was no horizontal pleiotropy. Heterogeneity was evaluated by Cochran's Q, which indicated no heterogeneity. In a multivariate MR study with seven sleep characteristics corrected for each other, we found that sleep duration remained causally associated with AD (OR = 1.004, 95 % CI: 1.000-1.007). Moreover, we found that after mutual correction, daytime napping had a causal relationship with the onset of AD, and daytime napping may reduce the risk of AD (OR = 0.995, 95 % CI: 0.991-1.000). CONCLUSION: This study is helpful for the early identification and prediction of risk factors for AD, long sleep durations are a risk factor for AD, and daytime napping can reduce the risk of AD.

Elucidating sleep disorders: a comprehensive bioinformatics analysis of functional gene sets and hub genes.

Background: Sleep disorders (SD) are known to have a profound impact on human health and quality of life although their exact pathogenic mechanisms remain poorly understood. Methods: The study first accessed SD datasets from the GEO and identified DEGs. These DEGs were then subjected to gene set enrichment analysis. Several advanced techniques, including the RF, SVM-RFE, PPI networks, and LASSO methodologies, were utilized to identify hub genes closely associated with SD. Additionally, the ssGSEA approach was employed to analyze immune cell infiltration and functional gene set scores in SD. DEGs were also scrutinized in relation to miRNA, and the DGIdb database was used to explore potential pharmacological treatments for SD. Furthermore, in an SD murine model, the expression levels of these hub genes were confirmed through RT-qPCR and Western Blot analyses. Results: The findings of the study indicate that DEGs are significantly enriched in functions and pathways related to immune cell activity, stress response, and neural system regulation. The analysis of immunoinfiltration demonstrated a marked elevation in the levels of Activated CD4+ T cells and CD8+ T cells in the SD cohort, accompanied by a notable rise in Central memory CD4 T cells, Central memory CD8 T cells, and Natural killer T cells. Using machine learning algorithms, the study also identified hub genes closely associated with SD, including IPO9, RAP2A, DDX17, MBNL2, PIK3AP1, and ZNF385A. Based on these genes, an SD diagnostic model was constructed and its efficacy validated across multiple datasets. In the SD murine model, the mRNA and protein expressions of these 6 hub genes were found to be consistent with the results of the bioinformatics analysis. Conclusion: In conclusion, this study identified 6 genes closely linked to SD, which may play pivotal roles in neural system development, the immune microenvironment, and inflammatory responses. Additionally, the key gene-based SD diagnostic model constructed in this study, validated on multiple datasets showed a high degree of reliability and accuracy, predicting its wide potential for clinical applications. However, limited by the range of data sources and sample size, this may affect the generalizability of the results.

Exploring the causal effects of sleep characteristics on TMD-related pain: a two-sample Mendelian randomization study.

OBJECTIVES: The study was to explore the causal effects of sleep characteristics on temporomandibular disorder (TMD)-related pain using Mendelian randomization (MR) analysis. MATERIALS AND METHODS: Five sleep characteristics (short sleep, insomnia, chronotype, snoring, sleep apnea) were designated as exposure factors. Data were obtained from previous publicized genome-wide association studies and single nucleotide polymorphisms (SNPs) strongly associated with them were utilized as instrumental variables (IVs). TMD-related pain was designed as outcome variable and sourced from the FinnGens database. MR analysis was employed to explore the causal effects of the five sleep characteristics on TMD-related pain. The causal effect was analyzed using the inverse variance-weighted (IVW), weighted median, and MR-Egger methods. Subsequently, sensitivity analyses were conducted using Cochran's Q tests, funnel plots, leave-one-out analyses, and MR-Egger intercept tests. RESULTS: A causal effect of short sleep on TMD-related pain was revealed by IVW (OR: 1.60, 95% CI: 1.06-2.41, P = 0.026). No causal relationship was identified between other sleep characteristics (insomnia, chronotype, snoring, sleep apnea) and TMD-related pain. CONCLUSIONS: Our study suggests that short sleep may increase the risk of TMD-related pain, while there was no causal relationship between other sleep characteristics and TMD-related pain. Further studies are warranted to deepen and definitively clarify their relationship. CLINICAL RELEVANCE: These findings reveal that the short sleep may be a risk factor of TMD-related pain and highlight the potential therapeutical effect of extending sleep time on alleviating TMD-related pain.

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

BACKGROUND: There is a profound connection between abnormal sleep patterns and brain disorders, suggesting a shared influential association. However, the shared genetic basis and potential causal relationships between sleep-related traits and brain disorders are yet to be fully elucidated. METHODS: Utilizing linkage disequilibrium score regression (LDSC) and bidirectional two-sample univariable Mendelian Randomization (UVMR) analyses with large-scale GWAS datasets, we investigated the genetic correlations and causal associations across six sleep traits and 24 prevalent brain disorders. Additionally, a multivariable Mendelian Randomization (MVMR) analysis evaluated the cumulative effects of various sleep traits on each brain disorder, complemented by genetic loci characterization to pinpoint pertinent genes and pathways. RESULTS: LDSC analysis identified significant genetic correlations in 66 out of 144 (45.8 %) pairs between sleep-related traits and brain disorders, with the most pronounced correlations observed in psychiatric disorders (66 %, 48/72). UVMR analysis identified 29 causal relationships (FDR<0.05) between sleep traits and brain disorders, with 19 associations newly discovered according to our knowledge. Notably, major depression, attention-deficit/hyperactivity disorder, bipolar disorder, cannabis use disorder, and anorexia nervosa showed bidirectional causal relations with sleep traits, especially insomnia's marked influence on major depression (IVW beta 0.468, FDR = 5.24E-09). MVMR analysis revealed a nuanced interplay among various sleep traits and their impact on brain disorders. Genetic loci characterization underscored potential genes, such as HOXB2, while further enrichment analyses illuminated the importance of synaptic processes in these relationships. CONCLUSIONS: This study provides compelling evidence for the causal relationships and shared genetic backgrounds between common sleep-related traits and brain disorders.

Causal association of sleep traits with the risk of thyroid cancer: A mendelian randomization study.

BACKGROUND: This study was to explore the causal associations of sleep traits including sleep duration, snoring, chronotype, sleep disorders, getting up in the morning, sleeplessness/insomnia and nap during day with the risk of thyroid cancer based on Mendelian randomization (MR) analysis. METHOD: Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published genome-wide association studies (GWASs) using the FinnGen and UK Biobank databases. A series of screening processes were performed to select qualified SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the Mendelian Randomization robust adjusted profile score (MR-RAPS), the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and the Weighted Median to estimate the causal links between sleep traits and the risk of thyroid cancer. Odds ratio (OR) and 95% confidence interval (CI) were calculated. RESULTS: The IVW results showed that getting up in the morning (OR = 0.055, 95%CI: 0.004-0.741) and napping during day (OR = 0.031, 95%CI: 0.002-0.462) were associated with decreased risk of thyroid cancer in the Italian population. A 1.30-h decrease of sleep duration was associated with 7.307-fold of thyroid cancer risk in the Finnish population (OR = 7.307, 95%CI: 1.642-32.519). Cronotype could decrease the risk of thyroid cancer in the Finnish population (OR = 0.282, 95%CI: 0.085-0.939). Sleep disorders increased the risk of thyroid cancer in the Finnish population (OR = 2.298, 95%CI: 1.194-4.422). The combined results revealed that sleep duration was correlated with increased risk of thyroid cancer (OR = 5.600, 95%CI: 1.458-21.486). CONCLUSION: Decreased sleep duration was associated with increased risk of thyroid cancer, which indicated the importance of adequate sleep for the prevention of thyroid cancer.

A genome-wide association study identifies candidate genes for sleep disturbances in depressed individuals.

OBJECTIVE: This study aimed to identify candidate loci and genes related to sleep disturbances in depressed individuals and clarify the co-occurrence of sleep disturbances and depression from the genetic perspective. METHODS: The study subjects (including 58,256 self-reported depressed individuals and 6,576 participants with PHQ-9 score ≥ 10, respectively) were collected from the UK Biobank, which were determined based on the Patient Health Questionnaire (PHQ-9) and self-reported depression status, respectively. Sleep related traits included chronotype, insomnia, snoring and daytime dozing. Genome-wide association studies (GWASs) of sleep related traits in depressed individuals were conducted by PLINK 2.0 adjusting age, sex, Townsend deprivation index and 10 principal components as covariates. The CAUSALdb database was used to explore the mental traits associated with the candidate genes identified by the GWAS. RESULTS: GWAS detected 15 loci significantly associated with chronotype in the subjects with self-reported depression, such as rs12736689 at RNASEL (P = 1.00 × 10- 09), rs509476 at RGS16 (P = 1.58 × 10- 09) and rs1006751 at RFX4 (P = 1.54 × 10- 08). 9 candidate loci were identified in the subjects with PHQ-9 ≥ 10, of which 2 loci were associated with insomnia such as rs115379847 at EVC2 (P = 3.50 × 10- 08), and 7 loci were associated with daytime dozing, such as rs140876133 at SMYD3 (P = 3.88 × 10- 08) and rs139156969 at ROBO2 (P = 3.58 × 10- 08). Multiple identified genes, such as RNASEL, RGS16, RFX4 and ROBO2 were reported to be associated with chronotype, depression or cognition in previous studies. CONCLUSION: Our study identified several candidate genes related to sleep disturbances in depressed individuals, which provided new clues for understanding the biological mechanism underlying the co-occurrence of depression and sleep disorders.

Causality between sleep traits and the risk of frailty: a Mendelian randomization study.

Background: Research based on observation has demonstrated a relationship between sleep traits and frailty; however, it remains uncertain if this correlation indicates causation. The purpose of this study was to look at the causal relationship that exists between frailty and sleep traits. Method: Using summaries from a genome-wide association study of self-reported sleep features and frailty index, we performed a bidirectional Mendelian randomization (MR) analysis. Examining the causal relationships between seven sleep-related traits and frailty was the goal. The major method used to calculate effect estimates was the inverse-variance weighted method, supplemented by the weighted median and MR-Egger approaches. The study investigated pleiotropy and heterogeneity using several methodologies, such as the MR-Egger intercept, the MR-PRESSO approach, and the Cochran's Q test. We took multivariate Mendelian randomization and genetic correlations between related traits to enhance the confidence of the results. Furthermore, we used MRlap to correct for any estimation bias due to sample overlap. Results: Insomnia, napping during the day, and sleep apnea syndrome exhibited a positive connection with the frailty index in forward MR analysis. Conversely, there is a negative link between getting up in the morning, snoring and sleep duration with the frailty index. During the reverse MR analysis, the frailty index exhibited a positive correlation with insomnia, napping during the day, and sleep apnea syndrome, while demonstrating a negative correlation with sleep duration. There was no direct correlation between snoring, chronotype, and frailty. In MVMR analyses, the causal effect of sleep characteristics on frailty indices remained consistent after adjusting for potential confounders including BMI, smoking, and triglycerides. Conclusion: The findings of our investigation yield novel evidence that substantiates the notion of a bidirectional causal connection between sleep traits and frailty. Through the optimization of sleep, it is potentially feasible to hinder, postpone, or even reverse the state of frailty, and we proposed relevant interventions.

Shared genetic mechanisms underlying association between sleep disturbances and depressive symptoms.

OBJECTIVES: Polygenic scores (PGS) for sleep disturbances and depressive symptoms in an epidemiological cohort were contrasted. The overlap between genes assigned to variants that compose the PGS predictions was tested to explore the shared genetic bases of sleep problems and depressive symptoms. METHODS: PGS analysis was performed on the São Paulo Epidemiologic Sleep Study (EPISONO, N = 1042), an adult epidemiological sample. A genome wide association study (GWAS) for depression grounded the PGS calculations for Beck Depression Index (BDI), while insomnia GWAS based the PGS for Insomnia Severity Index (ISI) and Pittsburg Sleep Quality Index (PSQI). Pearson's correlation was applied to contrast PGS and clinical scores. Fisher's Exact and Benjamin-Hochberg tests were used to verify the overlaps between PGS-associated genes and the pathways enriched among their intersections. RESULTS: All PGS models were significant when individuals were divided as cases or controls according to BDI (R2 = 1.2%, p = 0.00026), PSQI (R2 = 3.3%, p = 0.007) and ISI (R2 = 3.4%, p = 0.021) scales. When clinical scales were used as continuous variables, the PGS models for BDI (R2 = 1.5%, p = 0.0004) and PSQI scores (R2 = 3.3%, p = 0.0057) reached statistical significance. PSQI and BDI scores were correlated, and the same observation was applied to their PGS. Genes assigned to variants that compose the best-fit PGS predictions for sleep quality and depressive symptoms were significantly overlapped. Pathways enriched among the intersect genes are related to synapse function. CONCLUSIONS: The genetic bases of sleep quality and depressive symptoms are correlated; their implicated genes are significantly overlapped and converge on neural pathways. This data suggests that sleep complaints accompanying depressive symptoms are not secondary issues, but part of the core mental illness.

Combined exome and whole transcriptome sequencing identifies a de novo intronic SRCAP variant causing DEHMBA syndrome with severe sleep disorder.

Rare heterozygous variants in exons 33-34 of the SRCAP gene are associated with Floating-Harbor syndrome and have a dominant-negative mechanism of action. At variance, heterozygous null alleles falling in other parts of the same gene cause developmental delay, hypotonia, musculoskeletal defects, and behavioral abnormalities (DEHMBA) syndrome. We report an 18-year-old man with DEHMBA syndrome and obstructive sleep apnea, who underwent exome sequencing (ES) and whole transcriptome sequencing (WTS) on peripheral blood. Trio analysis prioritized the de novo heterozygous c.5658+5 G > A variant. WTS promptly demostrated four different abnormal transcripts affecting >40% of the reads, three of which leading to a frameshift. This study demonstrated the efficacy of a combined ES-WTS approach in solving undiagnosed cases. We also speculated that sleep respiratory disorder may be an underdiagnosed complication of DEHMBA syndrome.

Causal effects of sleep traits on metabolic syndrome and its components: a Mendelian randomization study.

PURPOSE: Previous observational studies have suggested an association between sleep disturbance and metabolic syndrome (MetS). However, it remains unclear whether this association is causal. This study aims to investigate the causal effects of sleep-related traits on MetS using Mendelian randomization (MR). METHODS: Single-nucleotide polymorphisms strongly associated with daytime napping, insomnia, chronotype, short sleep, and long sleep were selected as genetic instruments from the corresponding genome-wide association studies (GWAS). Summary-level data for MetS were obtained from two independent GWAS datasets. Univariable and multivariable MR analyses were conducted to investigate and verify the causal effects of sleep traits on MetS. RESULTS: The univariable MR analysis demonstrated that genetically predicted daytime napping and insomnia were associated with increased risk of MetS in both discovery dataset (OR daytime napping = 1.630, 95% CI 1.273, 2.086; OR insomnia = 1.155, 95% CI 1.108, 1.204) and replication dataset (OR daytime napping = 1.325, 95% CI 1.131, 1.551; OR insomnia = 1.072, 95% CI 1.046, 1.099). For components, daytime napping was positively associated with triglycerides (beta = 0.383, 95% CI 0.160, 0.607) and waist circumference (beta = 0.383, 95% CI 0.184, 0.583). Insomnia was positively associated with hypertension (OR = 1.101, 95% CI 1.042, 1.162) and waist circumference (beta = 0.067, 95% CI 0.031, 0.104). The multivariable MR analysis indicated that the adverse effect of daytime napping and insomnia on MetS persisted after adjusting for BMI, smoking, drinking, and another sleep trait. CONCLUSION: Our study supported daytime napping and insomnia were potential causal factors for MetS characterized by central obesity, hypertension, or elevated triglycerides.

Exploring the molecular pathways linking sleep phenotypes and POGZ-associated neurodevelopmental disorder.

Pogo transposable element-derived protein with ZNF domain (POGZ) gene encodes a chromatin regulator and rare variants on this gene have been associated with a broad spectrum of neurodevelopmental disorders, such as White-Sutton syndrome. Patient clinical manifestations frequently include developmental delay, autism spectrum disorder and obesity. Sleep disturbances are also commonly observed in these patients, yet the biological pathways which link sleep traits to the POGZ-associated syndrome remain unclear. We screened for sleep implications among individuals with causative POGZ variants previously described. Sleep disturbances were observed in 52% of patients, and being obese was not observed as a risk factor for sleep problems. Next, we identified genes associated with sleep-associated traits among the POGZ regulatory targets, aiming to uncover the molecular pathways that, when disrupted by POGZ loss of function, contribute to the aetiology of sleep phenotypes in these patients. The intersect between POGZ targets and sleep-related genes was used in a pathway enrichment analysis. Relevant pathways among these overlapping genes are involved in the regulation of circadian rhythm, tau protein binding, ATPase activator activity. This study may represent the beginning for novel functional investigations on shared molecular mechanisms between sleep disturbances and rare developmental syndromes related to POGZ and its regulatory targets.

Assessing the journey of calcium supplementation: A mendelian randomization study on the causal link between calcium levels and sleep disorders.

BACKGROUND & AIM: Sleep disorder is a growing concern, and calcium supplementation is often recommended as a potential intervention for sleep disorders. However, the causal relationship between calcium levels and the incidence of sleep disorders remains unclear. Mendelian randomization techniques utilizing genetic variants that affect calcium levels, can provide valuable insights into causality. This study aims to examine the association between calcium levels and sleep disorders in a diverse population that includes both adolescents and adults, and investigate the effects of calcium levels on sleep disorders. METHODS: Mendelian randomization analysis was conducted using data from UK Biobank and FinnGen datasets. The inverse-variance weighting (IVW) was selected as the primary method. In addition, traditional mediation analysis was performed on a subset of the NHANES data spanning from 2007 to 2018. RESULTS: Our findings provide evidence supporting a causal relationship between calcium intake and reduced risk of sleep disorders (beta = -0.079, SE = 0.0395, P = 0.0457). While not reaching statistical significance, other MR methods such as weighted median and Mr-Egger exhibited similar directional trends. Analysis of the NHANES cohort revealed a negative association between calcium levels and the prevalence of sleep disorders in male, black, and physically active populations. However, this association was not observed in other demographic groups. CONCLUSION: Our results suggested that there is no significant correlation between calcium levels and sleep disorder in non-exercise populations. This raises concerns about the long-term high-dose calcium supplementation in clinical practice, which requires further investigation.

Association between alcohol consumption and sleep traits: observational and mendelian randomization studies in the UK biobank.

Previous studies have shown that excessive alcohol consumption is associated with poor sleep. However, the health risks of light-to-moderate alcohol consumption in relation to sleep traits (e.g., insomnia, snoring, sleep duration and chronotype) remain undefined, and their causality is still unclear in the general population. To identify the association between alcohol consumption and multiple sleep traits using an observational and Mendelian randomization (MR) design. Observational analyses and one-sample MR (linear and nonlinear) were performed using clinical and individual-level genetic data from the UK Biobank (UKB). Two-sample MR was assessed using summary data from genome-wide association studies from the UKB and other external consortia. Phenotype analyses were externally validated using data from the National Health and Nutrition Examination Survey (2017-2018). Data analysis was conducted from January 2022 to October 2022. The association between alcohol consumption and six self-reported sleep traits (short sleep duration, long sleep duration, chronotype, snoring, waking up in the morning, and insomnia) were analysed. This study included 383,357 UKB participants (mean [SD] age, 57.0 [8.0] years; 46% male) who consumed a mean (SD) of 9.0 (10.0) standard drinks (one standard drink equivalent to 14 g of alcohol) per week. In the observational analyses, alcohol consumption was significantly associated with all sleep traits. Light-moderate-heavy alcohol consumption was linearly linked to snoring and the evening chronotype but nonlinearly associated with insomnia, sleep duration, and napping. In linear MR analyses, a 1-SD (14 g) increase in genetically predicted alcohol consumption was associated with a 1.14-fold (95% CI, 1.07-1.22) higher risk of snoring (P < 0.001), a 1.28-fold (95% CI, 1.20-1.37) higher risk of evening chronotype (P < 0.001) and a 1.24-fold (95% CI, 1.13-1.36) higher risk of difficulty waking up in the morning (P < 0.001). Nonlinear MR analyses did not reveal significant results after Bonferroni adjustment. The results of the two-sample MR analyses were consistent with those of the one-sample MR analyses, but with a slightly attenuated overall estimate. Our findings suggest that even low levels of alcohol consumption may affect sleep health, particularly by increasing the risk of snoring and evening chronotypes. The negative effects of alcohol consumption on sleep should be made clear to the public in order to promote public health.

Waking Up the Sleep Field: An Overview on the Implications of Genetics and Bioinformatics of Sleep.

Sleep genetics is an intriguing, as yet less understood, understudied, emerging area of biological and medical discipline. A generalist may not be aware of the current status of the field given the variety of journals that have published studies on the genetics of sleep and the circadian clock over the years. For researchers venturing into this fascinating area, this review thus includes fundamental features of circadian rhythm and genetic variables impacting sleep-wake cycles. Sleep/wake pathway medication exposure and susceptibility are influenced by genetic variations, and the responsiveness of sleep-related medicines is influenced by several functional polymorphisms. This review highlights the features of the circadian timing system and then a genetic perspective on wakefulness and sleep, as well as the relationship between sleep genetics and sleep disorders. Neurotransmission genes, as well as circadian and sleep/wake receptors, exhibit functional variability. Experiments on animals and humans have shown that these genetic variants impact clock systems, signaling pathways, nature, amount, duration, type, intensity, quality, and quantity of sleep. In this regard, the overview covers research on sleep genetics, the genomic properties of several popular model species used in sleep studies, homologs of mammalian genes, sleep disorders, and related genes. In addition, the study includes a brief discussion of sleep, narcolepsy, and restless legs syndrome from the viewpoint of a model organism. It is suggested that the understanding of genetic clues on sleep function and sleep disorders may, in future, result in an evidence-based, personalized treatment of sleep disorders.

Linking genetic foundations of sleep disturbances to personality traits: a study of mid-life twins.

Risk of sleep disturbances depends on individuals' personality, and a large body of evidence indicates that individuals prone to neuroticism, impulsivity, and (low) extraversion are more likely to experience them. Origins of these associations are unclear, but common genetic background may play an important role. Participants included 405 twin pairs (mean age of 54 years; 59% female) from the National Survey of Midlife Development in the United States (MIDUS) who reported on their personality traits (broad and specific), as well as sleep disturbances (problems with falling asleep, staying asleep, waking early, and feeling unrested). Uni- and bivariate biometric decompositions evaluated contributions of genetic and environmental factors to associations between personality and poor sleep, as well as unique contributions from individual traits. Neuroticism, extraversion, conscientiousness, and aggressiveness were the strongest phenotypic predictors of poor sleep. Genetic sources of covariance were about twice as large as non-shared environmental sources, and only shared genetic background accounted for links between aggressiveness and poor sleep. Neuroticism and extraversion accounted for most of the genetic overlap between personality and sleep disturbances. The findings shed light on developmental antecedents of ties between personality and poor sleep, suggesting a larger role of common genetic background than idiosyncratic life experiences. The results also suggest that emotion-related traits play the most important role for poor sleep, compared to other personality traits, and may partially account for genetic associations with other traits.

Genetics of sleep medication purchases suggests causality from sleep problems to psychiatric traits.

STUDY OBJECTIVES: Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems. METHODS: We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822). Post-association analyses included genetic correlation, co-localization, Mendelian randomization (MR), and polygenic risk estimation. RESULTS: In a GWAS we identified 27 genetic loci significantly associated with sleep medication, located in genes associated with sleep; AUTS2, CACNA1C, MEIS1, KIRREL3, PAX8, GABRA2, psychiatric traits; CACNA1C, HIST1H2BD, NUDT12. TOPAZ1 and TSNARE1. Co-localization and expression analysis emphasized effects on the KPNA2, GABRA2, and CACNA1C expression in the brain. Sleep medications use was epidemiologically related to psychiatric traits in FinnGen (OR [95% (CI)] = 3.86 [3.78 to 3.94], p < 2 × 10-16), and the association was accentuated by genetic correlation and MR; depression (rg = 0.55 (0.027), p = 2.86 × 10-89, p MR = 4.5 × 10-5), schizophrenia (rg = 0.25 (0.026), p = 2.52 × 10-21, p MR = 2 × 10-4), and anxiety (rg = 0.44 (0.047), p = 2.88 × 10-27, p MR = 8.6 × 10-12). CONCLUSIONS: These results demonstrate the genetics behind sleep problems and the association between sleep problems and psychiatric traits. Our results highlight the scientific basis for sleep management in treating the impact of psychiatric diseases.

PER2 gene and its association with sleep-related disorders: A review.

The natural circadian rhythm in an individual governs the sleep-wake cycle over 24 h. Disruptions in this internal cycle can lead to major health hazards and sleep disorders. Reports suggest that at least 50 % of people worldwide suffer from sleep-related disorders. An increase in screen time, especially in the wake of the COVID-19 pandemic, is one of the external causative factors for this condition. While many factors govern the circadian clock and its aberrance, the PER2 gene has been strongly linked to chronotypes by many researchers. The current paper provides an extensive examination of key Single Nucleotide Polymorphisms within the PER2 gene and their potential connection to four major types of sleep disorders. This study investigates whether these SNPs play a causative role in sleep disorders or if they are solely associated with these conditions. Additionally, we explore whether these genetic variations exert a lifelong influence on these sleep patterns or if external triggers contribute to the development of sleep disorders. This gene is a crucial regulator of the circadian cycle responsible for the transcription of other clock genes. It regulates a variety of physiological systems such as metabolism, sleep, body temperature, blood pressure, endocrine, immunological, cardiovascular, and renal function. We aim to establish some clarity to the multifaceted nature of this gene, which is often overlooked, and seek to establish the mechanistic role of PER2 gene mutations in sleep disorders. This will improve further understanding, assessment, and treatment of these conditions in future.

No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy.

Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.