Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci

Changes in sleep patterns in people with a history of depression during the COVID-19 pandemic: a natural experiment

BACKGROUND

The COVID-19 pandemic, while a major stressor, increased flexibility in sleep-wake schedules.

OBJECTIVES

To investigate the impact of the pandemic on sleep patterns in people with a history of depression and identify sociodemographic, clinical or genetic predictors of those impacts.

METHODS

6453 adults from the Australian Genetics of Depression Study (45±15 years; 75% women) completed surveys before (2016-2018) and during the pandemic (2020-2021). Participants were assigned to 'short sleep' (<6 hours), 'optimal sleep' (6-8 hours) or 'long sleep' (>8 hours). We focused on those having prepandemic 'optimal sleep'.

FINDINGS

Pre pandemic, the majority (70%, n=4514) reported optimal sleep, decreasing to 49% (n=3189) during the pandemic. Of these, 57% maintained optimal sleep, while 16% (n=725) shifted to 'short sleep' and 27% (n=1225) to 'long sleep'. In group comparisons 'optimal-to-short sleep' group had worse prepandemic mental health and increased insomnia (p's<0.001), along with an elevated depression genetic score (p=0.002). The 'optimal-to-long sleep' group were slightly younger and had higher distress (p's<0.05), a greater propensity to being evening types (p<0.001) and an elevated depression genetic score (p=0.04). Multivariate predictors for 'optimal-to-short sleep' included reported stressful life events, psychological or somatic distress and insomnia severity (false discovery rate-corrected p values<0.004), while no significant predictors were identified for 'optimal-to-long sleep'.

CONCLUSION AND IMPLICATIONS

The COVID-19 pandemic, a natural experiment, elicited significant shifts in sleep patterns among people with a history of depression, revealing associations with diverse prepandemic demographic and clinical characteristics. Understanding these dynamics may inform the selection of interventions for people with depression facing major challenges.

Causal relationship between neuroticism and frailty: A bidirectional Mendelian randomization study

BACKGROUND

Observational studies have shown that neuroticism is associated with frailty, but the causal relationship between them remains unclear.

METHODS

A two-sample Mendelian randomization (MR) study was conducted to explore the bidirectional causal relationship between neuroticism (n = 380,506 for the primary analysis, n = 79,004 for the validation) and frailty (n = 175,226) using publicly available genome-wide association study data. The inverse variance weighted (IVW), weighted median, and MR-Egger were used to obtain the causal estimates. Findings were verified through extensive sensitivity analyses and validated using another dataset. Multivariable MR (MVMR) analysis was performed to estimate the direct causal effects with adjustment of potential confounders. Two-step MR technique was then conducted to explore the mediators in the causal effects of neuroticism on frailty.

RESULTS

Genetically-predicted higher neuroticism score was significantly correlated with higher frailty index (IVW beta: 0.53, 95%CI: 0.48 to 0.59, P = 9.3E-83), and genetically-determined higher frailty index was significantly associated with higher neuroticism score (IVW beta: 0.28, 95%CI: 0.21 to 0.35, P = 1.3E-16). These results remained robust across sensitivity analyses and were reproducible using another dataset. The MVMR analysis indicated that the causal relationships remained significant after adjusting for the potential confounding factors. Mediation analysis revealed that depression, years of schooling, and smoking were significantly mediated the causal effects of neuroticism on frailty.

CONCLUSIONS

A bidirectional causal relationship existed between neuroticism and frailty. Our findings suggested that early intervention and behavioral changes might be helpful to reduce the neuroticism levels and prevent the development of frailty.

Fibroblasts as an in vitro model of circadian genetic and genomic studies

Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established in vitro model for measuring circadian patterns. We set out to examine the underlying genetic architecture of circadian rhythm in fibroblasts, with the goal to assess its contribution to the polygenic nature of BD disease risk. We collected, from primary cell lines of 6 healthy individuals, temporal genomic features over a 48 h period from transcriptomic data (RNA-seq) and open chromatin data (ATAC-seq). The RNA-seq data showed that only a limited number of genes, primarily the known core clock genes such as ARNTL, CRY1, PER3, NR1D2 and TEF display circadian patterns of expression consistently across cell cultures. The ATAC-seq data identified that distinct transcription factor families, like those with the basic helix-loop-helix motif, were associated with regions that were increasing in accessibility over time. Whereas known glucocorticoid receptor target motifs were identified in those regions that were decreasing in accessibility. Further evaluation of these regions using stratified linkage disequilibrium score regression analysis failed to identify a significant presence of them in the known genetic architecture of BD, and other psychiatric disorders or neurobehavioral traits in which the circadian rhythm is affected. In this study, we characterize the biological pathways that are activated in this in vitro circadian model, evaluating the relevance of these processes in the context of the genetic architecture of BD and other disorders, highlighting its limitations and future applications for circadian genomic studies.

Causal Relationship Between Micronutrient and Sleep Disorder: A Mendelian Randomization Study

Background

Sleep played an important part in human health, and COVID-19 led to a continuous deterioration of sleep. However, the causal relationship between micronutrient and sleep disorder was not yet fully understood.

Methods

In this research, the genetic causal relationship between micronutrient and sleep disorder was analyzed utilizing a two-sample Mendelian randomization (MR). Single nucleotide polymorphisms (SNPs) were used as instrumental variables. The analyses were conducted using the MR-Egger, inverse variance weighted, weighted mode, weighted median, simple mode, Cochran's Q test and leave-one-out.

Results

Our results suggested that 8 genetically predicted micronutrients participated in sleep disorders, including liver iron (L-iron) and iron in sleeping too much, spleen iron (S-iron) in sleeplessness/insomnia, trouble falling or staying asleep, sleep duration (undersleepers) and nonorganic sleeping disorders, iron metabolism disorder (IMD) and vitamin B12 deficiency anaemia (VB12DA) in narcolepsy, urine sodium (uNa) in narcolepsy, sleep apnea syndrome and sleep disorder, vitamin D (VD) in sleep duration (oversleepers), 25-Hydroxyvitamin D (25(OH)D) in trouble falling or staying asleep.

Conclusion

Our study used Mendelian randomization methods at the SNP level to explore the potential causal relationship among L-iron, iron, S-iron, IMD, uNa, 25(OH)D, VD, VB12DA with certain sleep disorder subtypes. Our results uncovered a micronutrient-based strategy for alleviating sleep disorder symptoms.

Genetic and Modifiable Risk Factors for Postoperative Complications of Total Joint Arthroplasty: A Genome-Wide Association and Mendelian Randomization Study

Background: Total joint arthroplasty (TJA) is an orthopedic procedure commonly used to treat damaged joints. Despite the efficacy of TJA, postoperative complications, including aseptic prosthesis loosening and infections, are common. Moreover, the effects of individual genetic susceptibility and modifiable risk factors on these complications are unclear. This study analyzed these effects to enhance patient prognosis and postoperative management. Methods: We conducted an extensive genome-wide association study (GWAS) and Mendelian randomization (MR) study using UK Biobank data. The cohort included 2964 patients with mechanical complications post-TJA, 957 with periprosthetic joint infection (PJI), and a control group of 398,708 individuals. Genetic loci associated with postoperative complications were identified by a GWAS analysis, and the causal relationships of 11 modifiable risk factors with complications were assessed using MR. Results: The GWAS analysis identified nine loci associated with post-TJA complications. Two loci near the PPP1R3B and RBM26 genes were significantly linked to mechanical complications and PJI, respectively. The MR analysis demonstrated that body mass index was positively associated with the risk of mechanical complications (odds ratio [OR]: 1.42; p < 0.001). Higher educational attainment was associated with a decreased risk of mechanical complications (OR: 0.55; p < 0.001) and PJI (OR: 0.43; p = 0.001). Type 2 diabetes was suggestively associated with mechanical complications (OR, 1.18, p = 0.02), and hypertension was suggestively associated with PJI (OR, 1.41, p = 0.008). Other lifestyle factors, including smoking and alcohol consumption, were not causally related to postoperative complications. Conclusions: The genetic loci near PPP1R3B and RBM26 influenced the risk of post-TJA mechanical complications and infections, respectively. The effects of genetic and modifiable risk factors, including body mass index and educational attainment, underscore the need to perform personalized preoperative assessments and the postoperative management of surgical patients. These results indicate that integrating genetic screening and lifestyle interventions into patient care can improve the outcomes of TJA and patient quality of life.

The Genetics of Human Sleep and Sleep Disorders

Healthy sleep is vital for humans to achieve optimal health and longevity. Poor sleep and sleep disorders are strongly associated with increased morbidity and mortality. However, the importance of good sleep continues to be underrecognized. Mechanisms regulating sleep and its functions in humans remain mostly unclear even after decades of dedicated research. Advancements in gene sequencing techniques and computational methodologies have paved the way for various genetic analysis approaches, which have provided some insights into human sleep genetics. This review summarizes our current knowledge of the genetic basis underlying human sleep traits and sleep disorders. We also highlight the use of animal models to validate genetic findings from human sleep studies and discuss potential molecular mechanisms and signaling pathways involved in the regulation of human sleep.

Genetic correlation and causal relationship between sleep and myopia: a mendelian randomization study

Purpose

To investigate the genetic correlation and causal links between sleep traits (including sleep duration, chronotype, and insomnia) and myopia.

Methods

Summary data on three sleep traits (sleep duration, chronotype and insomnia) and myopia from FinnGen (n = 214,211) and UK Biobank (n = 460,536) were analyzed using linkage disequilibrium score regression (LD Score), univariable and multivariable mendelian randomization (MR) experiments and Causal Analysis Using Summary Effect (CAUSE) estimation.

Results

LD Score regression detected candidate genetic correlation between sleep traits and myopia, such as sleep duration, chronotype (Genetic Correlation Z-score >10.00, h2_observed_p < 0.005, Lambda GC > 1.05, p > 0.05). Univariable MR analyses indicated that increased sleep duration has a promotional effect on the occurrence of myopia (p = 0.046 < 0.05, P_FDR = 0.138 < 0.2, OR = 2.872, 95% CI: 1.018-8.101). However, after accounting for potential confounding factors, multivariable MR and CAUSE analysis did not provide evidence for a causal effect of the three sleep traits on myopia.

Conclusion

There may be a potential genetic correlation between sleep duration, chronotype and myopia. However, neither of sleep duration, chronotype or insomnia had causal effect on myopia.

The circadian system: A neglected player in neurodevelopmental disorders

Patients with neurodevelopmental disorders, such as autism spectrum disorder, often display abnormal circadian rhythms. The role of the circadian system in these disorders has gained considerable attention over the last decades. Yet, it remains largely unknown how these disruptions occur and to what extent they contribute to the disorders' development. In this review, we examine circadian system dysregulation as observed in patients and animal models of neurodevelopmental disorders. Second, we explore whether circadian rhythm disruptions constitute a risk factor for neurodevelopmental disorders from studies in humans and model organisms. Lastly, we focus on the impact of psychiatric medications on circadian rhythms and the potential benefits of chronotherapy. The literature reveals that patients with neurodevelopmental disorders display altered sleep-wake cycles and melatonin rhythms/levels in a heterogeneous manner, and model organisms used to study these disorders appear to support that circadian dysfunction may be an inherent characteristic of neurodevelopmental disorders. Furthermore, the pre-clinical and clinical evidence indicates that circadian disruption at the environmental and genetic levels may contribute to the behavioural changes observed in these disorders. Finally, studies suggest that psychiatric medications, particularly those prescribed for attention-deficit/hyperactivity disorder and schizophrenia, can have direct effects on the circadian system and that chronotherapy may be leveraged to offset some of these side effects. This review highlights that circadian system dysfunction is likely a core pathological feature of neurodevelopmental disorders and that further research is required to elucidate this relationship.

The role of circadian rhythms and sleep in the aetiology of autism spectrum disorder and attention-deficit/hyperactivity disorder: New evidence from bidirectional two-sample Mendelian randomization analysis

LAY ABSTRACT

Research shows that people with autism spectrum disorder and attention-deficit/hyperactivity disorder often have sleep issues and problems with the body's natural daily rhythms, known as circadian rhythms. By exploring the genetic variants associated with these rhythms and the conditions, this study reveals that these rhythm changes and sleep patterns are directly linked to autism spectrum disorder and attention-deficit/hyperactivity disorder. It found that the timing of one's most active hours can increase the likelihood of having both autism spectrum disorder and attention-deficit/hyperactivity disorder. Importantly, it also shows that good sleep quality might protect against autism spectrum disorder, while disturbed sleep in people with attention-deficit/hyperactivity disorder seems to be a result rather than the cause of the condition. This understanding can help doctors and researchers develop better treatment approaches that focus on the specific ways sleep and body rhythms affect those with autism spectrum disorder and attention-deficit/hyperactivity disorder, considering their unique associations with circadian rhythms and sleep patterns. Understanding these unique links can lead to more effective, personalized care for those affected by these conditions.

Association between sleep traits and sarcopenia-related traits: A two-sample bidirectional Mendelian randomization study

AIM

Despite limited evidence regarding the impact of sleep quality on sarcopenia, it is widely recognized as being associated with various diseases. This study aimed to explore the causal relationship between sleep traits and sarcopenia-related traits.

METHODS

This study utilized a two-sample bidirectional Mendelian randomization analysis. Genetic genome-wide summary data of sleep quality indicators, including chronotype, morning wake-up time, sleep duration, daytime napping, insomnia and daytime dozing, were used. Data on sarcopenia-related traits, such as appendicular lean mass, grip strength of both hands, walking pace and waist circumference, were collected from a large cohort study. The primary method used was the inverse-variance weighted analysis.

RESULTS

A causal association was found between chronotype and appendicular lean mass (odds ratio [OR] 1.019, 95% confidence interval [CI] 1.016-1.211, P = 0.021). Napping during the day was connected with walking pace (OR 0.879, 95% CI 0.834-0.928, P = 2.289 × 10-6) and waist circumference (OR 1.234, 95% CI 1.081-1.408, P = 0.002). Insomnia was related to lower grip strength of the right hand (OR 0.844, 95% CI 0.747-0.954, P = 0.007), left hand (OR 0.836, 95% CI 0.742-0.943, P = 0.003), as well as walking pace (OR 0.871, 95% CI 0.798-0.951, P = 0.002). Furthermore, the reverse Mendelian randomization analysis showed associations between certain sarcopenia-related traits and poor sleep quality.

CONCLUSIONS

Some sleep traits were associated with the occurrence of sarcopenia. These findings emphasized the significance of prioritizing sleep quality as a preventive measure against sarcopenia. Geriatr Gerontol Int 2024; 24: 537-545.

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.

Causal association between type 2 diabetes mellitus and acute suppurative otitis media: insights from a univariate and multivariate Mendelian randomization study

Background

Type 2 diabetes mellitus (T2DM) and hearing loss (HL) constitute significant public health challenges worldwide. Recently, the association between T2DM and HL has aroused attention. However, possible residual confounding factors and other biases inherent to observational study designs make this association undetermined. In this study, we performed univariate and multivariable Mendelian Randomization (MR) analysis to elucidate the causal association between T2DM and common hearing disorders that lead to HL.

Methods

Our study employed univariate and multivariable MR analyses, with the Inverse Variance Weighted method as the primary approach to assessing the potential causal association between T2DM and hearing disorders. We selected 164 and 9 genetic variants representing T2DM from the NHGRI-EBI and DIAGRAM consortium, respectively. Summary-level data for 10 hearing disorders were obtained from over 500,000 participants in the FinnGen consortium and MRC-IEU. Sensitivity analysis revealed no significant heterogeneity of instrumental variables or pleiotropy was detected.

Results

In univariate MR analysis, genetically predicted T2DM from both sources was associated with an increased risk of acute suppurative otitis media (ASOM) (In NHGRI-EBI: OR = 1.07, 95% CI: 1.02-1.13, P = 0.012; In DIAGRAM: OR = 1.14, 95% CI: 1.02-1.26, P = 0.016). Multivariable MR analysis, adjusting for genetically predicted sleep duration, alcohol consumption, body mass index, and smoking, either individually or collectively, maintained these associations. Sensitivity analyses confirmed the robustness of the results.

Conclusion

T2DM was associated with an increased risk of ASOM. Strict glycemic control is essential for the minimization of the effects of T2DM on ASOM.

KAT8 beyond Acetylation: A Survey of Its Epigenetic Regulation, Genetic Variability, and Implications for Human Health

Lysine acetyltransferase 8, also known as KAT8, is an enzyme involved in epigenetic regulation, primarily recognized for its ability to modulate histone acetylation. This review presents an overview of KAT8, emphasizing its biological functions, which impact many cellular processes and range from chromatin remodeling to genetic and epigenetic regulation. In many model systems, KAT8's acetylation of histone H4 lysine 16 (H4K16) is critical for chromatin structure modification, which influences gene expression, cell proliferation, differentiation, and apoptosis. Furthermore, this review summarizes the observed genetic variability within the KAT8 gene, underscoring the implications of various single nucleotide polymorphisms (SNPs) that affect its functional efficacy and are linked to diverse phenotypic outcomes, ranging from metabolic traits to neurological disorders. Advanced insights into the structural biology of KAT8 reveal its interaction with multiprotein assemblies, such as the male-specific lethal (MSL) and non-specific lethal (NSL) complexes, which regulate a wide range of transcriptional activities and developmental functions. Additionally, this review focuses on KAT8's roles in cellular homeostasis, stem cell identity, DNA damage repair, and immune response, highlighting its potential as a therapeutic target. The implications of KAT8 in health and disease, as evidenced by recent studies, affirm its importance in cellular physiology and human pathology.

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.

Sleep regulation and host genetics

Due to the multifactorial and complex nature of rest, we focus on phenotypes related to sleep. Sleep regulation is a multifactorial process. In this chapter, we focus on those phenotypes inherent to sleep that are highly prevalent in the population, and that can be modulated by lifestyle, such as sleep quality and duration, insomnia, restless leg syndrome and daytime sleepiness. We, therefore, leave in the background those phenotypes that constitute infrequent pathologies or for which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Similarly, the regulation of sleep quality is intimately linked to the regulation of the circadian rhythm. Although this relationship is discussed in the sections that require it, the in-depth study of circadian rhythm regulation at the molecular level deserves a separate chapter, and this is how it is dealt with in this volume.

The relationship between autoimmune thyroid disease, thyroid nodules and sleep traits: a Mendelian randomization study

Background

Previous studies have suggested a potential association between Autoimmune thyroid disease Thyroid nodules and Sleep Traits, but the evidence is limited and controversial, and the exact causal relationship remains uncertain.

Objective

Therefore, we employed a MR analysis to investigate the causal relationship between Autoimmune thyroid disease, Thyroid nodules and Sleep Traits.

Methods

To explore the interplay between Autoimmune thyroid disease Thyroid nodules and Sleep Traits, we employed MR studies utilizing summary statistics derived from GWAS in individuals of European ancestry. To ensure robustness, multiple techniques were employed to assess the stability of the causal effect, including random-effect inverse variance weighted, weighted median, MR-Egger regression, and MR-PRESSO. Heterogeneity was evaluated using Cochran's Q value. Additionally, we investigated the presence of horizontal pleiotropy through MR-Egger regression and MR-PRESSO.

Results

The IVW method indicates a significant causal relationship between "Getting up" and autoimmune hypothyroidism, as revealed by the IVW method (OR: 0.59, 95% CI: 0.45 to 0.78, P-value = 1.99e-4). Additionally, there might be a potential correlation between sleep duration and autoimmune hypothyroidism (OR: 0.76, 95% CI: 0.60 to 0.79, P-value = 0.024). Moreover, the observed potential positive link between daytime nap and thyroid nodules (OR: 1.66, 95% CI: 1.07 to 2.58, P-value = 0.023) is subject to caution, as subsequent MR PRESSO testing reveals the presence of horizontal pleiotropy, raising concerns about the reliability of the findings. The findings suggested a potential inverse association between Autoimmune hypothyroidism and Getting up (OR: 0.99, 95% CI: 0.98 to 1.00, P-value = 6.66e-3).As the results of MR-Egger method(OR: 1.00, 95% CI: 0.98 to 1.02, P-value = 0.742) exhibited an opposing trend to that observed with the IVW method and the results did not reach significance after P-value correction.

Conclusion

The results of our study reveal a notable cause-and-effect relationship between Getting up and Autoimmune hypothyroidism, indicating its potential role as a protective factor against this condition. However, no causal connection was observed between sleep traits and Graves' disease or Thyroid nodules.

Circadian rhythm and host genetics

This chapter aims to explore the usefulness of the latest advances in genetic studies in the field of the circadian system in the future development of individualised strategies for health improvement based on lifestyle intervention. Due to the multifactorial and complex nature of the circadian system, we focus on the highly prevalent phenotypes in the population that are key to understanding its biology from an evolutionary perspective and that can be modulated by lifestyle. Therefore, we leave in the background those phenotypes that constitute infrequent pathologies or in which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Therefore, from an evolutionary paradigm, this chapter addresses phenotypes such as morning chronotypes, evening chronotypes, extreme chronotypes, and other key concepts such as circadian rhythm amplitude, resilience to changes in circadian rhythm, and their relationships with pathologies associated with circadian rhythm imbalances.

Fibroblasts as an in vitro model of circadian genetic and genomic studies: A temporal analysis

Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established in vitro model for measuring circadian patterns. We set out to examine the underlying genetic architecture of circadian rhythm in fibroblasts, with the goal to assess its contribution to the polygenic nature of BD disease risk. We collected, from primary cell lines of 6 healthy individuals, temporal genomic features over a 48 hour period from transcriptomic data (RNA-seq) and open chromatin data (ATAC-seq). The RNA-seq data showed that only a limited number of genes, primarily the known core clock genes such as ARNTL, CRY1, PER3, NR1D2 and TEF display circadian patterns of expression consistently across cell cultures. The ATAC-seq data identified that distinct transcription factor families, like those with the basic helix-loop-helix motif, were associated with regions that were increasing in accessibility over time. Whereas known glucocorticoid receptor target motifs were identified in those regions that were decreasing in accessibility. Further evaluation of these regions using stratified linkage disequilibrium score regression (sLDSC) analysis failed to identify a significant presence of them in the known genetic architecture of BD, and other psychiatric disorders or neurobehavioral traits in which the circadian rhythm is affected. In this study, we characterize the biological pathways that are activated in this in vitro circadian model, evaluating the relevance of these processes in the context of the genetic architecture of BD and other disorders, highlighting its limitations and future applications for circadian genomic studies.

Exome sequencing identifies genes associated with sleep-related traits

Sleep is vital for human health and has a moderate heritability. Previous genome-wide association studies have limitations in capturing the role of rare genetic variants in sleep-related traits. Here we conducted a large-scale exome-wide association study of eight sleep-related traits (sleep duration, insomnia symptoms, chronotype, daytime sleepiness, daytime napping, ease of getting up in the morning, snoring and sleep apnoea) among 450,000 participants from UK Biobank. We identified 22 new genes associated with chronotype (ADGRL4, COL6A3, CLK4 and KRTAP3-3), daytime sleepiness (ST3GAL1 and ANKRD12), daytime napping (PLEKHM1, ANKRD12 and ZBTB21), snoring (WDR59) and sleep apnoea (13 genes). Notably, 20 of these genes were confirmed to be significantly associated with sleep disorders in the FinnGen cohort. Enrichment analysis revealed that these discovered genes were enriched in circadian rhythm and central nervous system neurons. Phenotypic association analysis showed that ANKRD12 was associated with cognition and inflammatory traits. Our results demonstrate the value of large-scale whole-exome analysis in understanding the genetic architecture of sleep-related traits and potential biological mechanisms.

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.

Role of polygenic risk scores in the association between chronotype and health risk behaviors

BACKGROUND

This study explores the association between chronotypes and adolescent health risk behaviors (HRBs) by testing how genetic background moderates these associations and clarifies the influence of chronotypes and polygenic risk score (PRS) on adolescent HRBs.

METHODS

Using VOS-viewer software to select the corresponding data, this study used knowledge domain mapping to identify and develop the research direction with respect to adolescent risk factor type. Next, DNA samples from 264 students were collected for low-depth whole-genome sequencing. The sequencing detected HRB risk loci, 49 single nucleotide polymorphisms based to significant SNP. Subsequently, PRSs were assessed and divided into low, moderate, and high genetic risk according to the tertiles and chronotypes and interaction models were constructed to evaluate the association of interaction effect and clustering of adolescent HRBs. The chronotypes and the association between CLOCK-PRS and HRBs were examined to explore the association between chronotypes and mental health and circadian CLOCK-PRS and HRBs.

RESULTS

Four prominent areas were displayed by clustering information fields in network and density visualization modes in VOS-viewer. The total score of evening chronotypes correlated with high-level clustering of HRBs in adolescents, co-occurrence, and mental health, and the difference was statistically significant. After controlling covariates, the results remained consistent. Three-way interactions between chronotype, age, and mental health were observed, and the differences were statistically significant. CLOCK-PRS was constructed to identify genetic susceptibility to the clustering of HRBs. The interaction of evening chronotypes and high genetic risk CLOCK-PRS was positively correlated with high-level clustering of HRBs and HRB co-occurrence in adolescents, and the difference was statistically significant. The interaction between the sub-dimensions of evening chronotypes and the high genetic CLOCK-PRS risk correlated with the outcome of the clustering of HRBs and HRB co-occurrence.

CONCLUSIONS

The interaction of PRS and chronotype and the HRBs in adolescents appear to have an association, and the three-way interaction between the CLOCK-PRS, chronotype, and mental health plays important roles for HRBs in adolescents.

Archaic Introgression Shaped Human Circadian Traits

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely, Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultraviolet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology and whether archaic introgression adaptively contributed to human chronotypes remain unknown. Here, we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, and RORC) and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among expression quantitative trait loci for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

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.

A conserved role for frizzled in sleep architecture

Previous studies of natural variants in Drosophila melanogaster implicated the Wnt signaling receptor frizzled in sleep. Given that the Wnt signaling pathway is highly conserved across species, we hypothesized that frizzled class receptor 1 (Fzd1), the murine homolog of frizzled, would also have a role in sleep. Using a CRISPR transgenic approach, we removed most of the Fzd1 coding region from C57BL/6N mice. We used a video assay to measure sleep characteristics in Fzd1-deficient mice. As Wnt signaling is known to affect visuospatial memory, we also examined the impact of the deletion on learning and memory using the novel object recognition (NOR) paradigm. Fzd1-deficient mice had altered sleep compared to littermate controls. The mice did not respond differently to the NOR paradigm compared to controls but did display anxiety-like behavior. Our strategy demonstrates that the study of natural variation in Drosophila sleep translates into candidate genes for sleep in vertebrate species such as the mouse.

An association study of clock genes with major depressive disorder

OBJECTIVE

To study the relationship between clock genes and Major Depressive Disorder (MDD).

METHODS

GEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expressed genes between MDD and healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) enrichment analysis were performed on the differential expressed clock genes. Lasso Regression and Support Vector Machine (SVM) method were used for screening the differential expressed clock genes. Logistic regression was used to establish a diagnostic model for depression with the screened genes. Receiver Operating Characteristic (ROC) Curve was used to verify the model. Gene differential expression analysis was performed for MDD with high scores and MDD with low scores in the diagnostic model. Gene Set Enrichment Analysis (GSEA) enrichment analysis was performed for differentially expressed genes. Single-gene GSEA was used to analyze each gene in the model separately. Cibersort method was used to analyze the immune infiltration of MDD and healthy controls, and the correlation between immune cells and clock genes was analyzed. Cytoscape was used to analyze the clock gene interaction network. The DGIdb website was used to predict potentially effective therapeutic drugs for clock genes closely related to MDD.

RESULTS

Six genes were identified by differential expression analysis of clock genes between MDD and healthy controls. GO and KEGG enrichment analysis of 6 genes showed that their pathways were concentrated such as circadian rhythm, rhythmic process, TGF - beta signaling pathway, longevity regulating pathway-multiple species, adipocytokine signaling pathway and so on. Lasso regression and SVM were used to screen out 5 clock genes (HDAC1, ID3, NFIL3, PRKAA1, TNF) for MDD. The diagnostic model of depression was established according to the 5 clock genes. The area under the curve (AUC) of the established depression diagnostic model was 0.686. Gene difference analysis was performed between MDD patients with high score of clock gene diagnostic model and MDD patients with low score. GSEA was performed for the differential genes showed that the most enriched pathways were:adipocytokine signaling pathway, TGF beta signaling pathway, oxidative phosphorylation, primary immunodeficiency, and so on. The single gene GSEA showed that the most enriched pathways were Toll like receptor signaling pathway, glucolipid metabolism, amino acid metabolism, neuroactive ligand receptor interaction, and so on. The results of immune infiltration analysis showed that NK cells resting and Macrophages M2 were different between MDD and control groups. In MDD, the gene closely related to NK cells resting was HDAC1, and the genes closely related to Macrophages M2 were HDAC1 and NFIL3. The RNA interactions network of clock genes shows that the regulation process is complex, which can provide a reference for subsequent related research. Potential therapeutic drugs predict display, among the 5 clock genes, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs.

CONCLUSION

Among all CLOCK genes, HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD. Among them, TNF, HDAC1, and PRKAA1 may have potential effective therapeutic drugs.

The genetics of falling susceptibility and identification of causal risk factors

Falls represent a huge health and economic burden. Whilst many factors are associated with fall risk (e.g. obesity and physical inactivity) there is limited evidence for the causal role of these risk factors. Here, we used hospital and general practitioner records in UK Biobank, deriving a balance specific fall phenotype in 20,789 cases and 180,658 controls, performed a Genome Wide Association Study (GWAS) and used Mendelian Randomisation (MR) to test causal pathways. GWAS indicated a small but significant SNP-based heritability (4.4%), identifying one variant (rs429358) in APOE at genome-wide significance (P < 5e-8). MR provided evidence for a causal role of higher BMI on higher fall risk even in the absence of adverse metabolic consequences. Depression and neuroticism predicted higher risk of falling, whilst higher hand grip strength and physical activity were protective. Our findings suggest promoting lower BMI, higher physical activity as well as psychological health is likely to reduce falls.

Emerging trends and hot spots of sleep and genetic research: a bibliometric analysis of publications from 2002 to 2022 in the field

Background

Sleep is an important biological process and has been linked to many diseases; however, very little is known about which and how genes control and regulate sleep. Although technology has seen significant development, this issue has still not been adequately resolved. Therefore, we conducted a bibliometric analysis to assess the progress in research on sleep quality and associated genes over the past 2 decades. Through our statistical data and discussions, we aimed to provide researchers with better research directions and ideas, thus promoting the advancement of this field.

Methods

On December 29, 2022, we utilized bibliometric techniques, such as co-cited and cluster analysis and keyword co-occurrence, using tools such as CiteSpace, VOSviewer, and the Online Analysis Platform of Literature Metrology (http://bibliometric.com/), to conduct a thorough examination of the relevant publications extracted from the Web of Science Core Collection (WoSCC). Our analysis aimed to identify the emerging trends and hot spots in this field while also predicting their potential development in future.

Results

Cluster analysis of the co-cited literature revealed the most popular terms relating to sleep quality and associated genes in the manner of cluster labels; these included genome-wide association studies (GWAS), circadian rhythms, obstructive sleep apnea (OSA), DNA methylation, and depression. Keyword burst detection suggested that obstructive sleep apnea, circadian clock, circadian genes, and polygenic risk score were newly emergent research hot spots.

Conclusion

Based on this bibliometric analysis of the publications in the last 20 years, a comprehensive analysis of the literature clarified the contributions, changes in research hot spots, and evolution of research techniques regarding sleep quality and associated genes. This research can provide medical staff and researchers with revelations into future directions of the study on the pathological mechanisms of sleep-related diseases.

Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration

Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression.

Causal Effects of Gut Microbiota on Sleep-Related Phenotypes: A Two-Sample Mendelian Randomization Study

Increasing evidence suggests a correlation between changes in the composition of gut microbiota and sleep-related phenotypes. However, it remains uncertain whether these associations indicate a causal relationship. The genome-wide association study summary statistics data of gut microbiota (n = 18,340) was downloaded from the MiBioGen consortium and the data of sleep-related phenotypes were derived from the UK Biobank, the Medical Research Council-Integrative Epidemiology Unit, Jones SE, the FinnGen consortium. To test and estimate the causal effect of gut microbiota on sleep traits, a two-sample Mendelian randomization (MR) approach using multiple methods was conducted. A series of sensitive analyses, such as horizontal pleiotropy analysis, heterogeneity test, MR Steiger directionality test and "leave-one-out" analysis as well as reverse MR analysis, were conducted to assess the robustness of MR results. The genus Anaerofilum has a negative causal effect on getting up in the morning (odd ratio = 0.977, 95% confidence interval: 0.965-0.988, p = 7.28 × 10-5). A higher abundance of order Enterobacteriales and family Enterobacteriaceae contributed to becoming an "evening person". Six and two taxa were causally associated with longer and shorter sleep duration, respectively. Specifically, two SCFA-produced genera including Lachnospiraceae UCG004 (odd ratio = 1.029, 95% confidence interval = 1.012-1.046, p = 6.11 × 10-4) and Odoribacter contribute to extending sleep duration. Two obesity-related genera such as Ruminococcus torques (odd ratio = 1.024, 95% confidence interval: 1.011-1.036, p = 1.74 × 10-4) and Senegalimassilia were found to be increased and decreased risk of snoring, respectively. In addition, we found two risk taxa of insomnia such as the order Selenomonadales and one of its classes called Negativicutes. All of the sensitive analysis and reverse MR analysis results indicated that our MR results were robust. Our study revealed the causal effect of gut microbiota on sleep and identified causal risk and protective taxa for chronotype, sleep duration, snoring and insomnia, which has the potential to provide new perspectives for future mechanistic and clinical investigations of microbiota-mediated sleep abnormal patterns and provide clues for developing potential microbiota-based intervention strategies for sleep-related conditions.

Multi-ancestry genome-wide analysis identifies shared genetic effects and common genetic variants for self-reported sleep duration

Both short (≤6 h per night) and long sleep duration (≥9 h per night) are associated with increased risk of chronic diseases. Despite evidence linking habitual sleep duration and risk of disease, the genetic determinants of sleep duration in the general population are poorly understood, especially outside of European (EUR) populations. Here, we report that a polygenic score of 78 European ancestry sleep duration single-nucleotide polymorphisms (SNPs) is associated with sleep duration in an African (n = 7288; P = 0.003), an East Asian (n = 13 618; P = 6 × 10-4) and a South Asian (n = 7485; P = 0.025) genetic ancestry cohort, but not in a Hispanic/Latino cohort (n = 8726; P = 0.71). Furthermore, in a pan-ancestry (N = 483 235) meta-analysis of genome-wide association studies (GWAS) for habitual sleep duration, 73 loci are associated with genome-wide statistical significance. Follow-up of five loci (near HACD2, COG5, PRR12, SH3RF1 and KCNQ5) identified expression-quantitative trait loci for PRR12 and COG5 in brain tissues and pleiotropic associations with cardiovascular and neuropsychiatric traits. Overall, our results suggest that the genetic basis of sleep duration is at least partially shared across diverse ancestry groups.

Nonlinear expression patterns and multiple shifts in gene network interactions underlie robust phenotypic change in Drosophila melanogaster selected for night sleep duration

All but the simplest phenotypes are believed to result from interactions between two or more genes forming complex networks of gene regulation. Sleep is a complex trait known to depend on the system of feedback loops of the circadian clock, and on many other genes; however, the main components regulating the phenotype and how they interact remain an unsolved puzzle. Genomic and transcriptomic data may well provide part of the answer, but a full account requires a suitable quantitative framework. Here we conducted an artificial selection experiment for sleep duration with RNA-seq data acquired each generation. The phenotypic results are robust across replicates and previous experiments, and the transcription data provides a high-resolution, time-course data set for the evolution of sleep-related gene expression. In addition to a Hierarchical Generalized Linear Model analysis of differential expression that accounts for experimental replicates we develop a flexible Gaussian Process model that estimates interactions between genes. 145 gene pairs are found to have interactions that are different from controls. Our method appears to be not only more specific than standard correlation metrics but also more sensitive, finding correlations not significant by other methods. Statistical predictions were compared to experimental data from public databases on gene interactions. Mutations of candidate genes implicated by our results affected night sleep, and gene expression profiles largely met predicted gene-gene interactions.

Effects of Physical Activity and Circadian Rhythm on SCL-90 Scores by Factors among College Students

OBJECTIVE

A study was conducted to investigate the effects of different levels of physical activity and circadian rhythm differences on the nine factors of obsessive-compulsive disorder, interpersonal sensitivity, depression, anxiety, hostility, phobia, paranoia, and psychoticism on the SCL-90 scale.

METHODS

A questionnaire and mathematical and statistical methods were used to conduct the study. Data were collected through a web-based cross-sectional survey of college students from three universities in Anhui. A statistical analysis of the collected data was conducted using mathematical and statistical methods.

RESULTS

A total of 1248 students were included in the statistics of this study. Binary logistic regression analysis revealed that low physical activity levels were associated with somatization (OR = 1.36, 95% CI = 0.95-1.94), obsessive-compulsive disorder (OR = 1.85, 95% CI = 1.25-2.75), interpersonal sensitivity (OR = 1.94, 95% CI = 1.30-2.88), depression (OR = 2.03, 95% CI = 1.31-3.16), anxiety (OR = 1.67, 95% CI = 1.03-2.69), hostility (OR = 1.80, 95% CI = 1.12-2.89), phobia (OR = 1.88, 95% CI = 1.20-2.94), and paranoia (OR = 2.23, 95% CI = 1.43-3.46). Circadian rhythm differences were associated with somatization (OR = 0.91, 95% CI = 0.87-0.96), obsessive-compulsive disorder (OR = 0.93, p < 0.01, 95% CI = 0.89-0.98), interpersonal sensitivity (OR = 0.90, 95% CI = 0.85-0.94), depression (OR = 0.92, 95% CI = 0.87-0.97), anxiety (OR = 0.89, 95% CI = 0.83-0.95), hostility (OR = 0.91, 95% CI = 0.86-0.97), phobia (OR = 0.87, 95% CI = 0.82-0.93), and paranoia (OR = 0.90, 95% CI = 0.85-0.95) were all negatively associated. In addition, gender was associated with somatization and obsessive-compulsive disorder (OR = 0.75, 95% CI = 0.57-0.98), depression (OR = 0.92, 95% CI = 0.87-0.97), and paranoia (OR = 0.55, 95% CI = 0.40-0.76).

CONCLUSIONS

Low-intensity physical activity was more likely to be associated with somatization, obsessive-compulsive disorder, relationship sensitivity, depression, anxiety, hostility, terror, and paranoia than high-intensity and moderate-intensity physical activity, and circadian rhythm differences showed that people who slept later (known as nocturnal) were more likely to have these problems.

Exploring the associations between the Morningness-Eveningness-Stability-Scale improved (MESSi) and the higher-order personality factors

Morningness-eveningness refers to individual differences in the sleep-wake cycle. Research indicates that morningness-eveningness is associated with the Big Five (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) and the Big Two (alpha-stability, beta-plasticity) personality factors. However, the latter has not yet been tested within the multidimensional approach to morningness-eveningness. In the present study, we have adapted the Morningness-Eveningness-Stability-Scale improved (MESSi) to Polish (https://osf.io/rcxb5) to explore the associations between its subscales (morning affect, eveningness, distinctness) and the Big Two personality traits in a sample of 1106 participants (559 women and 547 men) aged 18 to 55 (M = 36.26, SD = 9.90). In bivariate correlations, morning affect was positively related to alpha-stability and beta-plasticity, distinctness was correlated negatively with alpha-stability and beta-plasticity, while eveningness was positively correlated only with beta-plasticity. Furthermore, the confirmatory factor analysis supported the original three-factor structure of the Polish version of MESSi, while the associations with affect and the symptoms of depression and anxiety attested to its validity. Overall, the present study provides the first evidence for the associations between MESSi subscales and the Big Two personality traits, as well as shows a good fit of the three-factor structure of MESSi in the Polish population.

Chronotype in college science students is associated with behavioral choices and can fluctuate across a semester

Many students self-report that they are "night owls," which can result from neurodevelopmental delays in the circadian timing system. However, whether an individual considers themselves to be an evening-type versus a morning-type (self-reported chronotype) may also be influenced by academic demands (e.g. class start times, course load) and behavioral habits (e.g. bedtime social media use, late caffeine consumption, daytime napping). If so, then chronotype should be malleable. We surveyed 858 undergraduate students enrolled in demanding science courses at up to three time points. The survey assessed morning/evening chronotype, global sleep quality, academics, and behavioral habits. Evening and morning-type students showed similar demographics, stress levels, and academic demands. At baseline measurements, relative to morning-types, evening-types showed significantly worse sleep quality and duration as well as 22% greater bedtime social media usage, 27% greater daytime napping duration, and 46% greater likelihood of consuming caffeine after 5pm. These behavioral habits partially mediated the effects of self-reported chronotype on sleep quality/duration, even after controlling for demographic factors. Interestingly, 54 students reported switching from being at least moderate evening-types at baseline to being at least moderate morning-types later in the semester and 56 students showed the reverse pattern (6.3% of students switched from "definitely" one chronotype to the other chronotype). Evening-to-morning "chrono-switchers" consumed less caffeine after 5pm and showed significantly better sleep quantity/quality at the later timepoint. Thus, some students may consider themselves to be night owls in part because they consume caffeine later, take more daytime naps, or use more social media at bedtime. Experimental work is needed to determine whether nudging night owls to behave like morning larks results in better sleep health or academic achievement.

Sub-types of insomnia in adolescents: Insights from a quantitative/molecular twin study

Background

Insomnia with short sleep duration has been postulated as more severe than that accompanied by normal/long sleep length. While the short duration subtype is considered to have greater genetic influence than the other subtype, no studies have addressed this question. This study aimed to compare these subtypes in terms of: (1) the heritability of insomnia symptoms; (2) polygenic scores (PGS) for insomnia symptoms and sleep duration; (3) the associations between insomnia symptoms and a wide variety of traits/disorders.

Methods

The sample comprised 4000 pairs of twins aged 16 from the Twins Early Development Study. Twin models were fitted to estimate the heritability of insomnia in both groups. PGS were calculated for self-reported insomnia and sleep duration and compared among participants with short and normal/long sleep duration.

Results

Heritability was not significantly different in the short sleep duration group (A = 0.13 [95%CI = 0.01, 0.32]) and the normal/long sleep duration group (A = 0.35 [95%CI = 0.29, 0.40]). Shared environmental factors accounted for a substantial proportion of the variance in the short sleep duration group (C = 0.19 [95%CI = 0.05, 0.32]) but not in the normal/long sleep duration group (C = 0.00 [95%CI = 0.00, 0.04]). PGS did not differ significantly between groups although results were in the direction expected by the theory. Our results also showed that insomnia with short (as compared to normal/long) sleep duration had a stronger association with anxiety and depression (p < .05)-although not once adjusting for multiple testing.

Conclusions

We found mixed results in relation to the expected differences between the insomnia subtypes in adolescents. Future research needs to further establish cut-offs for 'short' sleep at different developmental stages and employ objective measures of sleep.

Modifiable pathways for longevity: A Mendelian randomization analysis

BACKGROUND

A variety of factors, including diet and lifestyle, obesity, physiology, metabolism, hormone levels, psychology, and inflammation, have been associated with longevity. The specific influences of these factors, however, are poorly understood. Here, possible causal relationships between putative modifiable risk factors and longevity are investigated.

METHODS

A random effects model was used to investigate the association between 25 putative risk factors and longevity. The study population comprised 11,262 long-lived subjects (≥90 years old, including 3484 individuals ≥99 years old) and 25,483 controls (≤60 years old), all of European ancestry. The data were obtained from the UK Biobank database. Genetic variations were used as instruments in two-sample Mendelian randomization to reduce bias. The odds ratios for genetically predicted SD unit increases were calculated for each putative risk factor. Egger regression was used to determine possible violations of the Mendelian randomization model.

RESULTS

Thirteen potential risk factors showed significant associations with longevity (≥90th) after correction for multiple testing. These included smoking initiation (OR:1.606; CI: 1.112-2.319) and educational attainment (OR:2.538, CI: 1.685-3.823) in the diet and lifestyle category, systolic and diastolic blood pressure (OR per SD increase: 0.518; CI: 0.438-0.614 for SBP and 0.620; CI 0.514-0.748 for DBP) and venous thromboembolism (OR:0.002; CI: 0.000-0.047) in the physiology category, obesity (OR: 0.874; CI: 0.796-0.960), BMI (OR per 1-SD increase: 0.691; CI: 0.628-0.760), and body size at age 10 (OR per 1-SD increase:0.728; CI: 0.595-0.890) in the obesity category, type 2 diabetes (T2D) (OR:0.854; CI: 0.816-0.894), LDL cholesterol (OR per 1-SD increase: 0.743; CI: 0.668-0.826), HDL cholesterol (OR per 1-SD increase: 1.243; CI: 1.112-1.390), total cholesterol (TC) (OR per 1-SD increase: 0.786; CI: 0.702-0.881), and triglycerides (TG) (OR per 1-SD increase: 0.865; CI: 0.749-0.998) in the metabolism category. Both longevity (≥90th) and super-longevity (≥99th), smoking initiation, body size at age 10, BMI, obesity, DBP, SBP, T2D, HDL, LDL, and TC were consistently associated with outcomes. The examination of underlying pathways found that BMI indirectly affected longevity through three pathways, namely, SBP, plasma lipids (HDL/TC/LDL), and T2D (p < 0.05).

CONCLUSION

BMI was found to significantly affect longevity through SBP, plasma lipid (HDL/TC/LDL), and T2D. Future strategies should focus on modifying BMI to improve health and longevity.

Upregulation of Tribbles decreases body weight and increases sleep duration

Eukaryotic Tribbles proteins are pseudoenzymes that regulate multiple aspects of intracellular signalling. Both Drosophila melanogaster and mammalian members of this family of pseudokinases act as negative regulators of insulin signalling. Mammalian tribbles pseudokinase (TRIB) genes have also been linked to insulin resistance and type 2 diabetes mellitus. Type 2 diabetes mellitus is associated with increased body weight, sleep problems and increased long-term mortality. Here, we investigated how manipulating the expression of Tribbles impacts body weight, sleep and mortality. We showed that the overexpression of Drosophila tribbles (trbl) in the fly fat body reduces both body weight and lifespan in adult flies without affecting food intake. Furthermore, it decreases the levels of Drosophila insulin-like peptide 2 (DILP2; ILP2) and increases night-time sleep. The three genes encoding TRIBs of mammals, TRIB1, TRIB2 and TRIB3, show both common and unique features. As the three human TRIB genes share features with Drosophila trbl, we further explored the links between TRIB genetic variants and both body weight and sleep in the human population. We identified associations between the polymorphisms and expression levels of the pseudokinases and markers of body weight and sleep duration. We conclude that Tribbles pseudokinases are involved in the control of body weight, lifespan and sleep.

Sleep behaviors and Parkinson's disease: A bidirectional Mendelian randomization analysis

OBJECTIVE

Whether the quantity and quality of sleep are the risk factors for the development of Parkinson's disease remains unclear though it has now been confirmed that the quality of sleep among patients with Parkinson's disease is affected at the prodromal and clinical stages. Accordingly, this study aimed to examine the bidirectional causal relationships of multiple sleep-related phenotypes with Parkinson's disease using a two-sample Mendelian randomization (MR) method.

METHODS

The summary-level data collected from the published genome-wide association studies was used for analysis. Besides, the genetic relationships between different sleep-related phenotypes, including self-reported and accelerometer measured traits, were estimated for the risk and age at the onset of Parkinson's disease. To conduct MR analysis, inverse variance weighted, weight median, MR-Egger, and MR-PRESSO method were mainly used. Moreover, sensitivity analyses were carried out to examine the pleiotropic effect.

RESULTS

In general, there was insufficient evidence to support the causal effect of sleep-related phenotypes on risk (N cases/controls = 33,674/449,056) and age at the onset (N cases = 28,568) of Parkinson's disease. However, the results of this study indicated that the later onset age of Parkinson's disease was related to the frequent occurrence of insomnia (OR [95% CI] 1.007 [1.003, 1.011], P < 0.001) after the adjustment for multiple testing.

CONCLUSIONS

The results of this study suggest that insomnia-associated single nucleotide polymorphisms are more frequent in later onset Parkinson's disease patients compared to earlier onset patients. However, given the limitations of statistical power and potential bias, further validation should be still conducted through larger population research.

Beyond sleep: A multidimensional model of chronotype

Chronotype can be defined as an expression or proxy for circadian rhythms of varied mechanisms, for example in body temperature, cortisol secretion, cognitive functions, eating and sleeping patterns. It is influenced by a range of internal (e.g., genetics) and external factors (e.g., light exposure), and has implications for health and well-being. Here, we present a critical review and synthesis of existing models of chronotype. Our observations reveal that most existing models and, as a consequence, associated measures of chronotype have focused solely or primarily on the sleep dimension, and typically have not incorporated social and environmental influences on chronotype. We propose a multidimensional model of chronotype, integrating individual (biological and psychological), environmental and social factors that appear to interact to determine an individual's true chronotype with potential feedback loops between these factors. This model could be beneficial not only from a basic science perspective but also in the context of understanding health and clinical implications of certain chronotypes as well as designing preventive and therapeutic approaches for related illnesses.

Genome-wide association study identifies four pan-ancestry loci for suicidal ideation in the Million Veteran Program

Suicidal ideation (SI) often precedes and predicts suicide attempt and death, is the most common suicidal phenotype and is over-represented in veterans. The genetic architecture of SI in the absence of suicide attempt (SA) is unknown, yet believed to have distinct and overlapping risk with other suicidal behaviors. We performed the first GWAS of SI without SA in the Million Veteran Program (MVP), identifying 99,814 SI cases from electronic health records without a history of SA or suicide death (SD) and 512,567 controls without SI, SA or SD. GWAS was performed separately in the four largest ancestry groups, controlling for sex, age and genetic substructure. Ancestry-specific results were combined via meta-analysis to identify pan-ancestry loci. Four genome-wide significant (GWS) loci were identified in the pan-ancestry meta-analysis with loci on chromosomes 6 and 9 associated with suicide attempt in an independent sample. Pan-ancestry gene-based analysis identified GWS associations with DRD2, DCC, FBXL19, BCL7C, CTF1, ANNK1, and EXD3. Gene-set analysis implicated synaptic and startle response pathways (q's<0.05). European ancestry (EA) analysis identified GWS loci on chromosomes 6 and 9, as well as GWS gene associations in EXD3, DRD2, and DCC. No other ancestry-specific GWS results were identified, underscoring the need to increase representation of diverse individuals. The genetic correlation of SI and SA within MVP was high (rG = 0.87; p = 1.09e-50), as well as with post-traumatic stress disorder (PTSD; rG = 0.78; p = 1.98e-95) and major depressive disorder (MDD; rG = 0.78; p = 8.33e-83). Conditional analysis on PTSD and MDD attenuated most pan-ancestry and EA GWS signals for SI without SA to nominal significance, with the exception of EXD3 which remained GWS. Our novel findings support a polygenic and complex architecture for SI without SA which is largely shared with SA and overlaps with psychiatric conditions frequently comorbid with suicidal behaviors.

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

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

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Genetics of circadian rhythms and sleep in human health and disease

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

Effects of Physical Activity and Circadian Rhythm Differences on the Mental Health of College Students in Schools Closed by COVID-19

Purpose: Since the prolonged sequestration management that was implemented in order to achieve lower infection and mortality rates, there has been a surge in depression worldwide. The correlation between the physical activity level and the detection rate of a depressed mood in college students should be of wide concern. A large number of studies have focused on the association between physical activity levels and a negative mood, but circadian rhythm differences seem to be strongly associated with both physical activity levels and mental illness. Therefore, this paper will examine the correlation between physical activity levels, circadian rhythm differences, and mental health levels in college students. METHODS: Data were collected through a web-based cross-sectional survey. In June and December 2022, questionnaires were administered to college students from three universities in Anhui, China. In addition to socio-demographic information, measures included the International Physical Activity Questionnaire-Short Form (IPAQ-SF), Morning and Evening Questionnaire-5 Items (MEQ-5), and Symptom Check List90 (SCL-90) scales. Correlation analysis was used to understand the relationship between physical activity and circadian rhythm differences in the three aspects of college student’s mental health. RESULTS: The analysis of the data led to the conclusion that 28.4% of the 1241 college students in this survey had psychological disorders. The physical activity level of male students was higher than that of female students, but the risk of having depressive tendencies was higher in female students than in male students. There was a significant negative correlation between the physical activity level and scl-90 scores (p < 0.01), which indicates that higher physical activity levels are associated with higher mental health. Circadian rhythm differences and scl-90 scores were significantly positively correlated among college students (p < 0.01), and night-type people had a higher risk of mental illness than intermediate-type and early-morning-type people. CONCLUSIONS: During the period of closed administration due to COVID-19, school college students experienced large and high levels of negative emotional phenomena due to reduced physical activity and public health emergencies. This study showed significant correlations between both physical activity levels and circadian rhythmicity differences and the degree of mental health of college students.

Role of chronotype in dietary intake, meal timing, and obesity: a systematic review

CONTEXT

Recent studies show that dietary habits and obesity seem to be influenced by chronotype, which reflects an individual's preference for the timing of sleeping, eating, and activity in a 24-hour period.

OBJECTIVE

This review aimed to analyze the association of chronotype with dietary habits, namely energy and macronutrient intakes, meal timing, and eating patterns, as well as with obesity.

DATA SOURCES

PubMed/MEDLINE, LILACS, and Google Scholar databases were searched between 2004 and 2020. Study selection was performed by 2 authors independently; disagreements on eligibility of articles were resolved by a third author. After assessment of 12 060 abstracts, 43 studies (21 articles on obesity; 13 on food consumption, meal timing, and eating patterns; and 9 that addressed both obesity and dietary behavior) were included.

DATA EXTRACTION

A standard form was used to extract study design, country, number of participants, method of chronotype determination, and main findings.

DATA ANALYSIS

Approximately 95% of included studies showed an association between eveningness and at least 1 unhealthy eating habit. Morningness was associated with regular consumption of fresh and minimally processed foods. In addition, about 47% of studies showed a higher association between late types and obesity.

CONCLUSION

Late types are more likely to present unhealthy eating habits, such as eating late at night, skipping breakfast often, and eating processed/ultraprocessed foods, while early types are more likely to have healthy and protective habits, such as eating early and eating predominantly fresh/minimally processed foods. Intermediate types tend to have a pattern of health and eating more similar to early types than to late types. Late types are also more likely to present higher weight and body mass index than early or intermediate types.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42021256078.

Causal association of sleep disturbances and low back pain: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous observational studies have shown that low back pain (LBP) often coexists with sleep disturbances, however, the causal relationship remains unclear. In the present study, the causal relationship between sleep disturbances and LBP was investigated and the importance of sleep improvement in the comprehensive management of LBP was emphasized.

METHODS

Genetic variants were extracted as instrumental variables (IVs) from the genome-wide association study (GWAS) of insomnia, sleep duration, short sleep duration, long sleep duration, and daytime sleepiness. Information regarding genetic variants in LBP was selected from a GWAS dataset and included 13,178 cases and 164,682 controls. MR-Egger, weighted median, inverse-variance weighted (IVW), penalized weighted median, and maximum likelihood (ML) were applied to assess the causal effects. Cochran's Q test and MR-Egger intercept were performed to estimate the heterogeneity and horizontal pleiotropy, respectively. Outliers were identified and eliminated based on MR-PRESSO analysis to reduce the effect of horizontal pleiotropy on the results. Removing each genetic variant using the leave-one-out analysis can help evaluate the stability of results. Finally, the reverse causal inference involving five sleep traits was implemented.

RESULTS

A causal relationship was observed between insomnia-LBP (OR = 1.954, 95% CI: 1.119-3.411), LBP-daytime sleepiness (OR = 1.011, 95% CI: 1.004-1.017), and LBP-insomnia (OR = 1.015, 95% CI: 1.004-1.026), however, the results of bidirectional MR analysis between other sleep traits and LBP were negative. The results of most heterogeneity tests were stable and specific evidence was not found to support the disturbance of horizontal multiplicity. Only one outlier was identified based on MR-PRESSO analysis.

CONCLUSION

The main results of our research showed a potential bidirectional causal association of genetically predicted insomnia with LBP. Sleep improvement may be important in comprehensive management of LBP.

Chrononutrition-When We Eat Is of the Essence in Tackling Obesity

Obesity is a chronic and relapsing public health problem with an extensive list of associated comorbidities. The worldwide prevalence of obesity has nearly tripled over the last five decades and continues to pose a serious threat to wider society and the wellbeing of future generations. The pathogenesis of obesity is complex but diet plays a key role in the onset and progression of the disease. The human diet has changed drastically across the globe, with an estimate that approximately 72% of the calories consumed today come from foods that were not part of our ancestral diets and are not compatible with our metabolism. Additionally, multiple nutrient-independent factors, e.g., cost, accessibility, behaviours, culture, education, work commitments, knowledge and societal set-up, influence our food choices and eating patterns. Much research has been focused on 'what to eat' or 'how much to eat' to reduce the obesity burden, but increasingly evidence indicates that 'when to eat' is fundamental to human metabolism. Aligning feeding patterns to the 24-h circadian clock that regulates a wide range of physiological and behavioural processes has multiple health-promoting effects with anti-obesity being a major part. This article explores the current understanding of the interactions between the body clocks, bioactive dietary components and the less appreciated role of meal timings in energy homeostasis and obesity.

What have we learned about sleep from selective breeding strategies?

Selective breeding is a classic technique that enables an experimenter to modify a heritable target trait as desired. Direct selective breeding for extreme sleep and circadian phenotypes in flies successfully alters these behaviors, and sleep and circadian perturbations emerge as correlated responses to selection for other traits in mice, rats, and dogs. The application of sequencing technologies to the process of selective breeding identifies the genetic network impacting the selected trait in a holistic way. Breeding techniques preserve the extreme phenotypes generated during selective breeding, generating community resources for further functional testing. Selective breeding is thus a unique strategy that can explore the phenotypic limits of sleep and circadian behavior, discover correlated responses of traits having shared genetic architecture with the target trait, identify naturally-occurring genomic variants and gene expression changes that affect trait variability, and pinpoint genes with conserved roles.

Sleep medicine: Practice, challenges and new frontiers

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.