Genome-Wide Association Study of Circadian Rhythmicity in 71,500 UK Biobank Participants and Polygenic Association with Mood Instability

Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements

STUDY OBJECTIVES

The diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome (CFS) is based on a constellation of symptoms which center around fatigue. However, fatigue is commonly reported in the general population by people without CFS. Does the biology underlying fatigue in patients with CFS also drive fatigue experienced by individuals without CFS?

METHODS

We used UK Biobank actigraphy data to characterize differences in physical activity patterns and daily temperature rhythms between participants diagnosed with CFS compared to controls. We then tested if single nucleotide variants (SNVs) previously associated with CFS are also associated with the variation of these actigraphic CFS correlates and/or subjective fatigue symptoms in the general population.

RESULTS

Participants diagnosed with CFS (n = 295) had significantly decreased overall movement (Cohen's d = 0.220, 95% CI of -0.335 to -0.106, p-value = 2.42 × 10-15), lower activity amplitudes (Cohen's d = -0.377, 95% CI of -0.492 to -0.262, p-value = 1.74 × 10-6), and lower wrist temperature amplitudes (Cohen's d = -0.173, 95% CI of -0.288 to -0.059, p-value = .002) compared to controls (n = 63,133). Of 30 tested SNVs associated in the literature with CFS, one was associated in the control population with subjective fatigue and one with actigraphic measurements (FDR < 0.05).

CONCLUSIONS

The genetic overlap of CFS risk with actigraphy and subjective fatigue phenotypes suggests that some biological mechanisms underlying pathologic fatigue in patients with CFS also underlie fatigue symptoms at a broader population level. Therefore, understanding the biology of fatigue in general may inform our understanding of CFS pathophysiology.

The interaction network and potential clinical effectiveness of dimensional psychopathology phenotyping based on EMR: a Bayesian network approach

The current DSM-oriented diagnostic paradigm has introduced the issue of heterogeneity, as it fails to account for the identification of the neurological processes underlying mental illnesses, which affects the precision of treatment. The Research Domain Criteria (RDoC) framework serves as a recognized approach to addressing this heterogeneity, and several assessment and translation techniques have been proposed. Among these methods, transforming RDoC scores from electronic medical records (EMR) using Natural Language Processing (NLP) has emerged as a suitable technique, demonstrating clinical effectiveness. Numerous studies have sought to use RDoC to understand the Diagnostic and Statistical Manual of Mental Disorders (DSM) categories from a qualified perspective, but few studies have examined the distribution variations and interaction characteristics of RDoC within various DSM categories through retrospective analyses. Therefore, we employed unsupervised learning to translate five domains of eRDoC scores derived from electronic medical records (EMR) of patients diagnosed with Major Depressive Disorder (MDD), Schizophrenia (SCZ), and Bipolar Disorder (BD) at West China Hospital between 2008 and 2021. The distribution characteristics, interaction networks, and potential clinical effectiveness of RDoC domains were analyzed. Using non-parametric statistical tests, we found that MDD had the highest score in Negative Valence System (NVS) (4.1, p < 0.001), while BD exhibited the highest score in Positive Valence System (PVS) score (4.9, p < 0.001) and Arousal System (AS) (4.4, p < 0.001). SCZ demonstrated the highest scores in Cognitive Systems (CS) (5.8, p < 0.001) and Social Processes Systems (SPS) (4.6, p < 0.001). Through Bayesian network (BN) analysis, we identified relatively consistent interaction relationships among various RDoC domains (NVS → AS, NVS → CS, NVS → PVS, as well as CS → SPS; parameter range = 0.156 to 0.635, p < 0.001). Lastly, using logistic regression and Cox proportional hazards models, we demonstrated that AS was significantly associated with the length of hospital stay (-0.21, p < 0.05) and 30-day readmission risk (adjusted odds ratio [aOR] = 0.91, 95% confidence interval [CI] 0.91-0.99) to some extent. In conclusion, we suggest that the eRDoC characteristics varied in different DSM. By Bayesian Network, we found NVS and CS might be potential source in interacting with other system. Furthermore, CS, SPS and AS were associated with the length of stay and 30-days readmission, making them effective for predicting prognosis of psychiatric disorders.

Relationship between Polygenic Risk Score and the Hypnotics in Bipolar I Disorder

Objective

Bipolar disorder (BD) is marked by significant change in mood and energy levels with sleep disturbance a common feature, resulting in diminished quality of life and impaired daily functioning. This study assessed the association between BD-polygenic risk scores (PRS) and hypnotics in bipolar I disorder (BD-I) patients.

Methods

Large-sample data were collected from the genome-wide association study of a multicenter Bipolar Genomic Study, and 1,394 BD-I patients with available medication information were divided into two groups depending on whether they used hypnotics or not. The Diagnostic Interview for Genetic Studies (DIGS) score was used to assess the clinical manifestations and function of the participants and the association between the use of hypnotics and genetic risk was analyzed.

Results

Of the 1,394 total participants, 556 (40%) patients received hypnotics, mostly benzodiazepines, administered singly or in combination with other sleeping agents such as, Z-drugs, melatonin-related drugs, and trazodone. The DIGS score was significantly higher for negative categories in the group prescribed hypnotics as was the BD-PRS score, according to the four p value thresholds (p = 0.3, 0.2, 0.1, and 0.05). Logistic regression analysis confirmed a statistically significant association between the BD-PRS and hypnotic use.

Conclusion

Our results suggest an association between hypnotic use and genetic susceptibility to BD. Sleep disturbances in participants were based on the prescription status of hypnotics supporting the hypothesis that sleep disturbances may be associated with genetic aspects of BD-I. Further genetic studies on genetic overlaps between BD and specific phenotypes or medication responses are required.

Navigating Challenges and Opportunities in Multi-Omics Integration for Personalized Healthcare

The field of multi-omics has witnessed unprecedented growth, converging multiple scientific disciplines and technological advances. This surge is evidenced by a more than doubling in multi-omics scientific publications within just two years (2022-2023) since its first referenced mention in 2002, as indexed by the National Library of Medicine. This emerging field has demonstrated its capability to provide comprehensive insights into complex biological systems, representing a transformative force in health diagnostics and therapeutic strategies. However, several challenges are evident when merging varied omics data sets and methodologies, interpreting vast data dimensions, streamlining longitudinal sampling and analysis, and addressing the ethical implications of managing sensitive health information. This review evaluates these challenges while spotlighting pivotal milestones: the development of targeted sampling methods, the use of artificial intelligence in formulating health indices, the integration of sophisticated n-of-1 statistical models such as digital twins, and the incorporation of blockchain technology for heightened data security. For multi-omics to truly revolutionize healthcare, it demands rigorous validation, tangible real-world applications, and smooth integration into existing healthcare infrastructures. It is imperative to address ethical dilemmas, paving the way for the realization of a future steered by omics-informed personalized medicine.

Using Polygenic Scores for Circadian Rhythms to Predict Wellbeing, Depressive Symptoms, Chronotype, and Health

The association between circadian rhythms and diseases has been well established, while the association with mental health is less explored. Given the heritable nature of circadian rhythms, this study aimed to investigate the relationship between genes underlying circadian rhythms and mental health outcomes, as well as a possible gene-environment correlation for circadian rhythms. Polygenic scores (PGSs) represent the genetic predisposition to develop a certain trait or disease. In a sample from the Netherlands Twin Register (N = 14,021), PGSs were calculated for two circadian rhythm measures: morningness and relative amplitude (RA). The PGSs were used to predict mental health outcomes such as subjective happiness, quality of life, and depressive symptoms. In addition, we performed the same prediction analysis in a within-family design in a subset of dizygotic twins. The PGS for morningness significantly predicted morningness (R2 = 1.55%) and depressive symptoms (R2 = 0.22%). The PGS for RA significantly predicted general health (R2 = 0.12%) and depressive symptoms (R2 = 0.20%). Item analysis of the depressive symptoms showed that 4 out of 14 items were significantly associated with the PGSs. Overall, the results showed that people with a genetic predisposition of being a morning person or with a high RA are likely to have fewer depressive symptoms. The four associated depressive symptoms described symptoms related to decision-making, energy, and feeling worthless or inferior, rather than sleep. Based on our findings future research should include a substantial role for circadian rhythms in depression research and should further explore the gene-environment correlation in circadian rhythms.

PROVIT-CLOCK: A Potential Influence of Probiotics and Vitamin B7 Add-On Treatment and Metabolites on Clock Gene Expression in Major Depression

INTRODUCTION

An increasing body of evidence suggests a strong relationship between gut health and mental state. Lately, a connection between butyrate-producing bacteria and sleep quality has been discussed. The PROVIT study, as a randomized, double-blind, 4-week, multispecies probiotic intervention study, aims at elucidating the potential interconnection between the gut's metabolome and the molecular clock in individuals with major depressive disorder (MDD).

METHODS

The aim of the PROVIT-CLOCK study was to analyze changes in core clock gene expression during treatment with probiotic intervention versus placebo in fasting blood and the connection with the serum- and stool-metabolome in patients with MDD (n = 53). In addition to clinical assessments in the PROVIT study, metabolomics analyses with 1H nuclear magnetic resonance spectroscopy (stool and serum) and gene expression (RT-qPCR) analysis of the core clock genes ARNTL, PER3, CLOCK, TIMELESS, NR1D1 in peripheral blood mononuclear cells of fasting blood were performed.

RESULTS

The gene expression levels of the clock gene CLOCK were significantly altered only in individuals receiving probiotic add-on treatment. TIMELESS and ARNTL gene expression changed significantly over the 4-week intervention period in both groups. Various positive and negative correlations between metabolites in serum/stool and core clock gene expression levels were observed.

CONCLUSION

Changing the gut microbiome by probiotic treatment potentially influences CLOCK gene expression. The preliminary results of the PROVIT-CLOCK study indicate a possible interconnection between the gut microbiome and circadian rhythm potentially orchestrated by metabolites.

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.

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.

The sleep-circadian interface: A window into mental disorders

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

The solute carrier SLC25A17 sustains peroxisomal redox homeostasis in diverse mammalian cell lines

Despite the crucial role of peroxisomes in cellular redox maintenance, little is known about how these organelles transport redox metabolites across their membrane. In this study, we sought to assess potential associations between the cellular redox landscape and the human peroxisomal solute carrier SLC25A17, also known as PMP34. This carrier has been reported to function as a counter-exchanger of adenine-containing cofactors such as coenzyme A (CoA), dephospho-CoA, flavin adenine dinucleotide, nicotinamide adenine dinucleotide (NAD+), adenosine 3',5'-diphosphate, flavin mononucleotide, and adenosine monophosphate. We found that inactivation of SLC25A17 resulted in a shift toward a more reductive state in the glutathione redox couple (GSSG/GSH) across HEK-293 cells, HeLa cells, and SV40-transformed mouse embryonic fibroblasts, with variable impact on the NADPH levels and the NAD+/NADH redox couple. This phenotype could be rescued by the expression of Candida boidinii Pmp47, a putative SLC25A17 orthologue reported to be essential for the metabolism of medium-chain fatty acids in yeast peroxisomes. In addition, we provide evidence that the alterations in the redox state are not caused by changes in peroxisomal antioxidant enzyme expression, catalase activity, H2O2 membrane permeability, or mitochondrial fitness. Furthermore, treating control and ΔSLC25A17 cells with dehydroepiandrosterone, a commonly used glucose-6-phosphate dehydrogenase inhibitor affecting NADPH regeneration, revealed a kinetic disconnection between the peroxisomal and cytosolic glutathione pools. Additionally, these experiments underscored the impact of SLC25A17 loss on peroxisomal NADPH metabolism. The relevance of these findings is discussed in the context of the still ambiguous substrate specificity of SLC25A17 and the recent observation that the mammalian peroxisomal membrane is readily permeable to both GSH and GSSG.

Quantifying the Association between Objectively Measured Physical Activity and Multiple Sclerosis in the UK Biobank

INTRODUCTION

Objectively measured physical activity (PA) data were collected in the accelerometry substudy of the UK Biobank. UK Biobank also contains information about multiple sclerosis (MS) diagnosis at the time of and after PA collection. This study aimed to 1) quantify the difference in PA between prevalent MS cases and matched healthy controls, and 2) evaluate the predictive performance of objective PA measures for incident MS cases.

METHODS

The first analysis compared eight accelerometer-derived PA summaries between MS patients ( N = 316) and matched controls (30 controls for each MS case). The second analysis focused on predicting time to MS diagnosis among participants who were not diagnosed with MS. A total of 19 predictors including eight measures of objective PA were compared using Cox proportional hazards models (number of events = 47; 585,900 person-years of follow-up).

RESULTS

In the prevalent MS study, the difference between MS cases and matched controls was statistically significant for all PA summaries ( P < 0.001). In the incident MS study, the most predictive variable of progression to MS in univariate Cox regression models was lower age ( C = 0.604), and the most predictive PA variable was lower relative amplitude (RA, C = 0.594). A two-stage forward selection using Cox regression resulted in a model with concordance C = 0.693 and four predictors: age ( P = 0.015), stroke ( P = 0.009), Townsend deprivation index ( P = 0.874), and RA ( P = 0.004). A model including age, stroke, and RA had a concordance of C = 0.691.

CONCLUSIONS

Objective PA summaries were significantly different and consistent with lower activity among study participants who had MS at the time of the accelerometry study. Among individuals who did not have MS, younger age, stroke history, and lower RA were significantly associated with a higher risk of a future MS diagnosis.

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.

Diurnal rhythms of wrist temperature are associated with future disease risk in the UK Biobank

Many chronic disease symptomatologies involve desynchronized sleep-wake cycles, indicative of disrupted biorhythms. This can be interrogated using body temperature rhythms, which have circadian as well as sleep-wake behavior/environmental evoked components. Here, we investigated the association of wrist temperature amplitudes with a future onset of disease in the UK Biobank one year after actigraphy. Among 425 disease conditions (range n = 200-6728) compared to controls (range n = 62,107-91,134), a total of 73 (17%) disease phenotypes were significantly associated with decreased amplitudes of wrist temperature (Benjamini-Hochberg FDR q < 0.05) and 26 (6.1%) PheCODEs passed a more stringent significance level (Bonferroni-correction α < 0.05). A two-standard deviation (1.8° Celsius) lower wrist temperature amplitude corresponded to hazard ratios of 1.91 (1.58-2.31 95% CI) for NAFLD, 1.69 (1.53-1.88) for type 2 diabetes, 1.25 (1.14-1.37) for renal failure, 1.23 (1.17-1.3) for hypertension, and 1.22 (1.11-1.33) for pneumonia (phenome-wide atlas available at http://bioinf.itmat.upenn.edu/biorhythm_atlas/ ). This work suggests peripheral thermoregulation as a digital biomarker.

CARE as a wearable derived feature linking circadian amplitude to human cognitive functions

Circadian rhythms are crucial for regulating physiological and behavioral processes. Pineal hormone melatonin is often used to measure circadian amplitude but its collection is costly and time-consuming. Wearable activity data are promising alternative, but the most commonly used measure, relative amplitude, is subject to behavioral masking. In this study, we firstly derive a feature named circadian activity rhythm energy (CARE) to better characterize circadian amplitude and validate CARE by correlating it with melatonin amplitude (Pearson's r = 0.46, P = 0.007) among 33 healthy participants. Then we investigate its association with cognitive functions in an adolescent dataset (Chinese SCHEDULE-A, n = 1703) and an adult dataset (UK Biobank, n = 92,202), and find that CARE is significantly associated with Global Executive Composite (β = 30.86, P = 0.016) in adolescents, and reasoning ability, short-term memory, and prospective memory (OR = 0.01, 3.42, and 11.47 respectively, all P < 0.001) in adults. Finally, we identify one genetic locus with 126 CARE-associated SNPs using the genome-wide association study, of which 109 variants are used as instrumental variables in the Mendelian Randomization analysis, and the results show a significant causal effect of CARE on reasoning ability, short-term memory, and prospective memory (β = -59.91, 7.94, and 16.85 respectively, all P < 0.0001). The present study suggests that CARE is an effective wearable-based metric of circadian amplitude with a strong genetic basis and clinical significance, and its adoption can facilitate future circadian studies and potential intervention strategies to improve circadian rhythms and cognitive functions.

Sexual dimorphism in the response to chronic circadian misalignment on a high-fat diet

Longitudinal studies associate shiftwork with cardiometabolic disorders but do not establish causation or elucidate mechanisms of disease. We developed a mouse model based on shiftwork schedules to study circadian misalignment in both sexes. Behavioral and transcriptional rhythmicity were preserved in female mice despite exposure to misalignment. Females were protected from the cardiometabolic impact of circadian misalignment on a high-fat diet seen in males. The liver transcriptome and proteome revealed discordant pathway perturbations between the sexes. Tissue-level changes were accompanied by gut microbiome dysbiosis only in male mice, biasing toward increased potential for diabetogenic branched chain amino acid production. Antibiotic ablation of the gut microbiota diminished the impact of misalignment. In the United Kingdom Biobank, females showed stronger circadian rhythmicity in activity and a lower incidence of metabolic syndrome than males among job-matched shiftworkers. Thus, we show that female mice are more resilient than males to chronic circadian misalignment and that these differences are conserved in humans.

Association between accelerometer-measured amplitude of rest-activity rhythm and future health risk: a prospective cohort study of the UK Biobank

BACKGROUND

The health effects of rest-activity rhythm are of major interest to public health, but its associations with health outcomes remain elusive. We aimed to examine the associations between accelerometer-measured rest-activity rhythm amplitude and health risks among the general UK population.

METHODS

We did a prospective cohort analysis of UK Biobank participants aged 43-79 years with valid wrist-worn accelerometer data. Low rest-activity rhythm amplitude was defined as the first quintile of relative amplitude; all other quintiles were classified as high rest-activity rhythm amplitude. Outcomes of interest were defined using International Classification of Diseases 10th Revision codes and consisted of incident cancer and cardiovascular, infectious, respiratory, and digestive diseases, and all-cause and disease-specific (cardiovascular, cancer, and respiratory) mortality. Participants with a current diagnosis of any outcome of interest were excluded. We assessed the associations between decreased rest-activity rhythm amplitude and outcomes using Cox proportional hazards models.

FINDINGS

Between June 1, 2013, and Dec 23, 2015, 103 682 participants with available raw accelerometer data were enrolled. 92 614 participants (52 219 [56·4%] women and 40 395 [42·6%] men) with a median age of 64 years (IQR 56-69) were recruited. Median follow-up was 6·4 years (IQR 5·8-6·9). Decreased rest-activity rhythm amplitude was significantly associated with increased incidence of cardiovascular diseases (adjusted hazard ratio 1·11 [95% CI 1·05-1·16]), cancer (1·08 [1·01-1·16]), infectious diseases (1·31 [1·22-1·41]), respiratory diseases (1·26 [1·19-1·34]), and digestive diseases (1·08 [1·03-1·14]), as well as all-cause mortality (1·54 [1·40-1·70]) and disease-specific mortality (1·73 [1·34-2·22] for cardiovascular diseases, 1·32 [1·13-1·55] for cancer, and 1·62 [1·25-2·09] for respiratory diseases). Most of these associations were not modified by age older than 65 years or sex. Among 16 accelerometer-measured rest-activity parameters, low rest-activity rhythm amplitude had the strongest or second- strongest associations with nine health outcomes.

INTERPRETATION

Our results suggest that low rest-activity rhythm amplitude might contribute to major health outcomes and provide further evidence to promote risk-modifying strategies associated with rest-activity rhythm to improve health and longevity.

FUNDING

National Natural Science Foundation of China and China Postdoctoral Science Foundation.

Does circadian dysrhythmia drive the switch into high- or low-activation states in bipolar I disorder?

OBJECTIVES

Emerging evidence suggests a role of circadian dysrhythmia in the switch between "activation" states (i.e., objective motor activity and subjective energy) in bipolar I disorder.

METHODS

We examined the evidence with respect to four relevant questions: (1) Are natural or environmental exposures that can disrupt circadian rhythms also related to the switch into high-/low-activation states? (2) Are circadian dysrhythmias (e.g., altered rest/activity rhythms) associated with the switch into activation states in bipolar disorder? (3) Do interventions that affect the circadian system also affect activation states? (4) Are associations between circadian dysrhythmias and activation states influenced by other "third" factors?

RESULTS

Factors that naturally or experimentally alter circadian rhythms (e.g., light exposure) have been shown to relate to activation states; however future studies need to measure circadian rhythms contemporaneously with these natural/experimental factors. Actigraphic measures of circadian dysrhythmias are associated prospectively with the switch into high- or low-activation states, and more studies are needed to establish the most relevant prognostic actigraphy metrics in bipolar disorder. Interventions that can affect the circadian system (e.g., light therapy, lithium) can also reduce the switch into high-/low-activation states. Whether circadian rhythms mediate these clinical effects is an unknown but valuable question. The influence of age, sex, and other confounders on these associations needs to be better characterised.

CONCLUSION

Based on the reviewed evidence, our view is that circadian dysrhythmia is a plausible driver of transitions into high- and low-activation states and deserves prioritisation in research in bipolar disorders.

Stronger Associations Between Sleep and Mental Health in Adults with Autism: A UK Biobank Study

This study examined sleep and its cognitive and affective correlates in adults with and without autism spectrum disorder (ASD), utilizing UK Biobank data. There were no group differences in subjective sleep duration [n = 220 ASD; n = 2200 general population (GP)]. Accelerometer measures of sleep duration or nighttime activity did not differ by group, but sleep efficiency was marginally lower in ASD (n = 83 ASD; n = 824 GP). Sleep efficiency was associated with wellbeing and mental health, and pathways between accelerometer sleep measures and wellbeing and mental health were significantly stronger for adults with ASD (who also reported substantially poorer wellbeing and > 5 × likelihood of experiencing mental distress). These findings highlight the need to monitor sleep to maintain good mental health in adult ASD.

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.

Depression and bipolar disorder subtypes differ in their genetic correlations with biological rhythms

Major Depression and Bipolar Disorder Type I (BIP-I) and Type II (BIP-II), are characterized by depressed, manic, and hypomanic episodes in which specific changes of physical activity, circadian rhythm, and sleep are observed. It is known that genetic factors contribute to variation in mood disorders and biological rhythms, but unclear to what extent there is an overlap between their underlying genetics. In the present study, data from genome-wide association studies were used to examine the genetic relationship between mood disorders and biological rhythms. We tested the genetic correlation of depression, BIP-I, and BIP-II with physical activity (overall physical activity, moderate activity, sedentary behaviour), circadian rhythm (relative amplitude), and sleep features (sleep duration, daytime sleepiness). Genetic correlations of depression, BIP-I, and BIP-II with biological rhythms were compared to discover commonalities and differences. A gene-based analysis tested for associations of single genes and common circadian genes with mood disorders. Depression was negatively correlated with overall physical activity and positively with sedentary behaviour, while BIP-I showed associations in the opposite direction. Depression and BIP-II had negative correlations with relative amplitude. All mood disorders were positively correlated with daytime sleepiness. Overall, we observed both genetic commonalities and differences across mood disorders in their relationships with biological rhythms: depression and BIP-I differed the most, while BIP-II was in an intermediate position. Gene-based analysis suggested potential targets for further investigation. The present results suggest shared genetic underpinnings for the clinically observed associations between mood disorders and biological rhythms. Research considering possible joint mechanisms may offer avenues for improving disease detection and treatment.

The impact of lithium on circadian rhythms and implications for bipolar disorder pharmacotherapy

Bipolar disorder (BD) is characterized by disrupted circadian rhythms affecting sleep, arousal, and mood. Lithium is among the most effective mood stabilizer treatments for BD, and in addition to improving mood symptoms, stabilizes sleep and activity rhythms in treatment responsive patients. Across a variety of experimental models, lithium has effects on circadian rhythms. However, uncertainty exists as to whether these actions directly pertain to lithium's therapeutic effects. Here, we consider evidence from mechanistic studies in animals and cells and clinical trials in BD patients that identify associations between circadian rhythms and the therapeutic effects of lithium. Most evidence indicates that lithium has effects on cellular circadian rhythms and increases morningness behaviors in BD patients, changes that may contribute to the therapeutic effects of lithium. However, much of this evidence is limited by cross-sectional analyses and/or imprecise proxy markers of clinical outcomes and circadian rhythms in BD patients, while mechanistic studies rely on inference from animals or small numbers of patients . Further study may clarify the essential mechanisms underlying lithium responsive BD, better characterize the longitudinal changes in circadian rhythms in BD patients, and inform the development of therapeutic interventions targeting circadian rhythms.

Correction of depression-associated circadian rhythm abnormalities is associated with lithium response in bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by episodes of depression and mania and disrupted circadian rhythms. Lithium is an effective therapy for BD, but only 30%-40% of patients are fully responsive. Preclinical models show that lithium alters circadian rhythms. However, it is unknown if the circadian rhythm effects of lithium are essential to its therapeutic properties.

METHODS

In secondary analyses of a multi-center, prospective, trial of lithium for BD, we examined the relationship between circadian rhythms and therapeutic response to lithium. Using standardized instruments, we measured morningness, diurnal changes in mood, sleep, and energy (circadian rhythm disturbances) in a cross-sectional study of 386 BD subjects with varying lithium exposure histories. Next, we tracked symptoms of depression and mania prospectively over 12 weeks in a subset of 88 BD patients initiating treatment with lithium. Total, circadian, and affective mood symptoms were scored separately and analyzed.

RESULTS

Subjects with no prior lithium exposure had the most circadian disruption, while patients stable on lithium monotherapy had the least. Patients who were stable on lithium with another drug or unstable on lithium showed intermediate levels of disruption. Treatment with lithium for 12 weeks yielded significant reductions in total and affective depression symptoms. Lithium responders (Li-Rs) showed improvement in circadian symptoms of depression, but non-responders did not. There was no difference between Li-Rs and nonresponders in affective, circadian, or total symptoms of mania.

CONCLUSIONS

Exposure to lithium is associated with reduced circadian disruption. Lithium response at 12 weeks was selectively associated with the reduction of circadian depressive symptoms. We conclude that stabilization of circadian rhythms may be an important feature of lithium's therapeutic effects.

CLINICAL TRIALS REGISTRY

NCT0127253.

Patterns of Convergence and Divergence Between Bipolar Disorder Type I and Type II: Evidence From Integrative Genomic Analyses

Aim: Genome-wide association studies (GWAS) analyses have revealed genetic evidence of bipolar disorder (BD), but little is known about the genetic structure of BD subtypes. We aimed to investigate the genetic overlap and distinction of bipolar type I (BD I) & type II (BD II) by conducting integrative post-GWAS analyses.

Methods: We utilized single nucleotide polymorphism (SNP)–level approaches to uncover correlated and distinct genetic loci. Transcriptome-wide association analyses (TWAS) were then approached to pinpoint functional genes expressed in specific brain tissues and blood. Next, we performed cross-phenotype analysis, including exploring the potential causal associations between two BD subtypes and lithium responses and comparing the difference in genetic structures among four different psychiatric traits.

Results: SNP-level evidence revealed three genomic loci, SLC25A17, ZNF184, and RPL10AP3, shared by BD I and II, and one locus (MAD1L1) and significant gene sets involved in calcium channel activity, neural and synapsed signals that distinguished two subtypes. TWAS data implicated different genes affecting BD I and II through expression in specific brain regions (nucleus accumbens for BD I). Cross-phenotype analyses indicated that BD I and II share continuous genetic structures with schizophrenia and major depressive disorder, which help fill the gaps left by the dichotomy of mental disorders.

Conclusion: These combined evidences illustrate genetic convergence and divergence between BD I and II and provide an underlying biological and trans-diagnostic insight into major psychiatric disorders.

Seasonal changes in mood and behavior contribute to suicidality and worthlessness in a population-based study

Limited evidence suggests that the seasonal changes in mood and behavior may associate with suicidality and the feelings of worthlessness, but these associations have not been analyzed in large population-based data. A random sample of adults (n = 4069), representative of the general population living in Finland, attended a nationwide health examination survey. Seasonal variations (seasonality) in mood and behavior were analyzed with the six items of global seasonality score (GSS) and the experienced problem due to these variations. Their impact on suicidality as well as on the feelings of worthlessness were analyzed using logistic regression models. After adjusting for age and gender, the GSS, each of its six items and the experienced problem due to the seasonal variations in mood and behavior all showed separately a significant association with suicidality as well as with worthlessness. After further adjustment for the education level and region of residence, the GSS, its mood item and the experienced problem remained significantly associated with both suicidality and worthlessness. Seasonal variations in mood and behavior have a significant association with both suicidality and worthlessness.

Neurobiological and behavioral mechanisms of circadian rhythm disruption in bipolar disorder: A critical multi-disciplinary literature review and agenda for future research from the ISBD task force on chronobiology

AIM

Symptoms of bipolar disorder (BD) include changes in mood, activity, energy, sleep, and appetite. Since many of these processes are regulated by circadian function, circadian rhythm disturbance has been examined as a biological feature underlying BD. The International Society for Bipolar Disorders Chronobiology Task Force (CTF) was commissioned to review evidence for neurobiological and behavioral mechanisms pertinent to BD.

METHOD

Drawing upon expertise in animal models, biomarkers, physiology, and behavior, CTF analyzed the relevant cross-disciplinary literature to precisely frame the discussion around circadian rhythm disruption in BD, highlight key findings, and for the first time integrate findings across levels of analysis to develop an internally consistent, coherent theoretical framework.

RESULTS

Evidence from multiple sources implicates the circadian system in mood regulation, with corresponding associations with BD diagnoses and mood-related traits reported across genetic, cellular, physiological, and behavioral domains. However, circadian disruption does not appear to be specific to BD and is present across a variety of high-risk, prodromal, and syndromic psychiatric disorders. Substantial variability and ambiguity among the definitions, concepts and assumptions underlying the research have limited replication and the emergence of consensus findings.

CONCLUSIONS

Future research in circadian rhythms and its role in BD is warranted. Well-powered studies that carefully define associations between BD-related and chronobiologically-related constructs, and integrate across levels of analysis will be most illuminating.

Rapid-acting antidepressants and the circadian clock

A growing number of epidemiological and experimental studies has established that circadian disruption is strongly associated with psychiatric disorders, including major depressive disorder (MDD). This association is becoming increasingly relevant considering that modern lifestyles, social zeitgebers (time cues) and genetic variants contribute to disrupting circadian rhythms that may lead to psychiatric disorders. Circadian abnormalities associated with MDD include dysregulated rhythms of sleep, temperature, hormonal secretions, and mood which are modulated by the molecular clock. Rapid-acting antidepressants such as subanesthetic ketamine and sleep deprivation therapy can improve symptoms within 24 h in a subset of depressed patients, in striking contrast to conventional treatments, which generally require weeks for a full clinical response. Importantly, animal data show that sleep deprivation and ketamine have overlapping effects on clock gene expression. Furthermore, emerging data implicate the circadian system as a critical component involved in rapid antidepressant responses via several intracellular signaling pathways such as GSK3β, mTOR, MAPK, and NOTCH to initiate synaptic plasticity. Future research on the relationship between depression and the circadian clock may contribute to the development of novel therapeutic strategies for depression-like symptoms. In this review we summarize recent evidence describing: (1) how the circadian clock is implicated in depression, (2) how clock genes may contribute to fast-acting antidepressants, and (3) the mechanistic links between the clock genes driving circadian rhythms and neuroplasticity.

pyActigraphy: Open-source python package for actigraphy data visualization and analysis

Over the past 40 years, actigraphy has been used to study rest-activity patterns in circadian rhythm and sleep research. Furthermore, considering its simplicity of use, there is a growing interest in the analysis of large population-based samples, using actigraphy. Here, we introduce pyActigraphy, a comprehensive toolbox for data visualization and analysis including multiple sleep detection algorithms and rest-activity rhythm variables. This open-source python package implements methods to read multiple data formats, quantify various properties of rest-activity rhythms, visualize sleep agendas, automatically detect rest periods and perform more advanced signal processing analyses. The development of this package aims to pave the way towards the establishment of a comprehensive open-source software suite, supported by a community of both developers and researchers, that would provide all the necessary tools for in-depth and large scale actigraphy data analyses.

The possibility to continuously record locomotor movements using accelerometers (actigraphy) has allowed field studies of sleep and rest-activity patterns. It has also enabled large-scale data collections, opening new avenues for research. However, each brand of actigraph devices encodes recordings in its own format and closed-source proprietary softwares are typically used to read and analyse actigraphy data. In order to provide an alternative to these softwares, we developed a comprehensive open-source toolbox for actigraphy data analysis, pyActigraphy. It allows researchers to read actigraphy data from 7 different file formats and gives access to a variety of rest-activity rhythm variables, automatic sleep detection algorithms and more advanced signal processing techniques. Besides, in order to empower researchers and clinicians with respect to their analyses, we created a series of interactive tutorials that illustrate how to implement the key steps of typical actigraphy data analyses. As an open-source project, all kind of user’s contributions to our toolbox are welcome. As increasing evidence points to the predicting value of rest-activity patterns derived from actigraphy for brain integrity, we believe that the development of the pyActigraphy package will not only benefit the sleep and chronobiology research, but also the neuroscientific community at large.

Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

BACKGROUND

Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort.

METHODS AND FINDINGS

In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures-bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration-were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = -0.11 (95% confidence interval -0.13 to -0.10, p = 3 × 10-56, FDR = 6 × 10-55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry.

CONCLUSIONS

In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

Data-driven modelling approach to circadian temperature rhythm profiles in free-living conditions

The individual variation in the circadian rhythms at the physiological level is not well understood. Albeit self-reported circadian preference profiles have been consolidated, their premises are grounded on human experience, not on physiology. We used data-driven, unsupervised time series modelling to characterize distinct profiles of the circadian rhythm measured from skin surface temperature in free-living conditions. We demonstrate the existence of three distinct clusters of individuals which differed in their circadian temperature profiles. The cluster with the highest temperature amplitude and the lowest midline estimating statistic of rhythm, or rhythm-adjusted mean, had the most regular and early-timed sleep–wake rhythm, and was the least probable for those with a concurrent delayed sleep phase, or eveningness chronotype. While the clusters associated with the observed sleep and circadian preference patterns, the entirely unsupervised modelling of physiological data provides a novel basis for modelling and understanding the human circadian functions in free-living conditions.

Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response: preliminary studies

Bipolar disorder (BD) is a neuropsychiatric illness defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. Lithium is an effective drug for BD, but 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, circadian rhythms have not been evaluated in BD patient neurons from Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients characterized for lithium responsiveness and matched controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R, but NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein levels were higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.

Circadian depression: A mood disorder phenotype

Major mood syndromes are among the most common and disabling mental disorders. However, a lack of clear delineation of their underlying pathophysiological mechanisms is a major barrier to prevention and optimised treatments. Dysfunction of the 24-h circadian system is a candidate mechanism that has genetic, behavioural, and neurobiological links to mood syndromes. Here, we outline evidence for a new clinical phenotype, which we have called 'circadian depression'. We propose that key clinical characteristics of circadian depression include disrupted 24-h sleep-wake cycles, reduced motor activity, low subjective energy, and weight gain. The illness course includes early age-of-onset, phenomena suggestive of bipolarity (defined by bidirectional associations between objective motor and subjective energy/mood states), poor response to conventional antidepressant medications, and concurrent cardiometabolic and inflammatory disturbances. Identifying this phenotype could be clinically valuable, as circadian-targeted strategies show promise for reducing depressive symptoms and stabilising illness course. Further investigation of underlying circadian disturbances in mood syndromes is needed to evaluate the clinical utility of this phenotype and guide the optimal use of circadian-targeted interventions.

Genomic perspectives on the circadian clock hypothesis of psychiatric disorders

Circadian rhythm disturbances are frequently described in psychiatric disorders such as major depressive disorder, bipolar disorder, and schizophrenia. Growing evidence suggests a biological connection between mental health and circadian rhythmicity, including the circadian influence on brain function and mood and the requirement for circadian entrainment by external factors, which is often impaired in mental illness. Mental (as well as physical) health is also adversely affected by circadian misalignment. The marked interindividual differences in this combined susceptibility, in addition to the phenotypic spectrum in traits related both to circadian rhythms and mental health, suggested the possibility of a shared genetic background and that circadian clock genes may also be candidate genes for psychiatric disorders. This hypothesis was further strengthened by observations in animal models where clock genes had been knocked out or mutated. The introduction of genome-wide association studies (GWAS) enabled hypothesis-free testing. GWAS analysis of chronotype confirmed the prominent role of circadian genes in these phenotypes and their extensive polygenicity. However, in GWAS on psychiatric traits, only one clock gene, ARNTL (BMAL1) was identified as one of the few loci differentiating bipolar disorder from schizophrenia, and macaque monkeys where the ARNTL gene has been knocked out display symptoms similar to schizophrenia. Another lesson from genomic analyses is that chronotype has an important genetic correlation with several psychiatric disorders and that this effect is unidirectional. We conclude that the effect of circadian disturbances on psychiatric disorders probably relates to modulation of rhythm parameters and extend beyond the core clock genes themselves.

Multiscale neurobiological correlates of human neuroticism

Neuroticism is a heritable personality trait associated with negative emotionality; however, we know little regarding the association between the microscale and macroscale neurobiological substrates of human neuroticism. Cross‐scale correlation analysis may provide such information. In this study, voxel‐wise neuroimaging–neuroticism correlation analyses consistently showed a positive correlation between neuroticism and functional connectivity density (FCD) in the ventral striatum in 274 young Chinese adults. Partial least squares regression analysis showed that the FCD‐neuroticism correlation map was significantly spatially correlated with gene expression profiles in each of six donated human brains. Neuroticism‐related genes derived from the six donors consistently showed significant enrichment in the chemical synaptic transmission, circadian entrainment, long‐term potentiation, inflammatory mediator regulation of transient receptor potential channels, and amphetamine addiction pathways. The protein–protein interaction analysis revealed four hub genes involved in the above pathways, including G protein subunit gamma 10, 5‐hydroxytryptamine receptor 2C, prodynorphin, and calcium/calmodulin‐dependent protein kinase II alpha. By combining multiscale correlation analyses and functional annotations, this study advances our understanding of the genetic and neural substrates of human neuroticism and emphasizes the importance of striatal functional properties in human neuroticism.

A genome-wide multiphenotypic association analysis identified common candidate genes for subjective well-being, depressive symptoms and neuroticism

Subjective well-being (SWB), depressive symptoms, and neuroticism are common and vital traits of mental disorders. Genetic mechanisms of SWB, depressive symptoms and neuroticism remain elusive now. The large-scale GWAS summary datasets of SWB (n = 229,883), depressive symptoms (n = 180,866), and neuroticism (n = 170,911) were obtained from published studies. MASH tool was applied to the GWAS datasets for identifying candidate SNPs shared by SWB, depressive symptoms and neuroticism. SNPs detected by MASH, were then mapped to target genes considering regulatory SNP (rSNP), methylated quantitative trait locus (MeQTL) and the SNPs near to known genes. Gene set enrichment analysis (GSEA) was conducted by the FUMA platform. A total of 122 candidate SNPs were detected by MASH analysis, mapping to 29 target genes, such as CLDN23, MSRA and XKR6. GO enrichment analysis identified multiple immune related gene sets for SWB, depressive symptoms and neuroticism, such as GSE2770_UNTREATED_VS_IL4_TREATED_ACT_CD4_TCELL_48H_DN (P = 7.32 × 10^-3), GSE6259_FLT3L_INDUCED_DEC205_POS_DC_VS_CD4_TCELL_DN (P = 2.52 × 10^-2). We also found some mental disorders related gene sets were associated with three phenotypes, such as mood instability (P = 1.15 × 10^-6) and neuroticism (P = 1.72 × 10^-6). We identified multiple candidate genes and GO terms shared by SWB, depressive symptoms and neuroticism. Our results support the overlapping genetic mechanisms, and suggest a functional correlation between immunity and SWB, depressive symptoms and neuroticism.

24-h Activity Rhythms and Health in Older Adults

Purpose of Review

Circadian rhythms, including 24-h activity rhythms, change with age. Disturbances in these 24-h activity rhythms at older age have also been implied in various diseases. This review evaluates recent findings on 24-h activity rhythms and disease in older adults.

Recent Findings

Growing evidence supports that 24-h activity rhythm disturbances at older age are related to the presence and/or progression of disease. Longitudinal and genetic work even suggests a potential causal contribution of disturbed 24-h activity rhythms to disease development. Interventional studies targeting circadian and 24-h activity rhythms demonstrate that 24-h rhythmicity can be improved, but the effect of improving 24-h rhythmicity on disease risk or progression remains to be shown.

Summary

Increasing evidence suggests that 24-h activity rhythms are involved in age-related diseases. Further studies are needed to assess causality, underlying mechanisms, and the effects of treating disturbed 24-h activity rhythms on age-related disease.

Using Chronobiological Phenotypes to Address Heterogeneity in Bipolar Disorder

Bipolar disorder (BD) is a neuropsychiatric mood disorder characterized by recurrent episodes of mania and depression in addition to disruptions in sleep, energy, appetite, and cognitive functions-rhythmic behaviors that typically change on daily cycles. BD symptoms can also be provoked by seasonal changes, sleep, and/or circadian disruption, indicating that chronobiological factors linked to the circadian clock may be a common feature in the disorder. Research indicates that BD exists on a clinical spectrum, with distinct subtypes often intersecting with other psychiatric disorders. This heterogeneity has been a major challenge to BD research and contributes to problems in diagnostic stability and treatment outcomes. To address this heterogeneity, we propose that chronobiologically related biomarkers could be useful in classifying BD into objectively measurable phenotypes to establish better diagnoses, inform treatments, and perhaps lead to better clinical outcomes. Presently, we review the biological basis of circadian time keeping in humans, discuss the links of BD to the circadian clock, and pre-sent recent studies that evaluated chronobiological measures as a basis for establishing BD phenotypes. We conclude that chronobiology may inform future research using other novel techniques such as genomics, cell biology, and advanced behavioral analyses to establish new and more biologically based BD phenotypes.

Polygenic score for neuroticism is related to sleep difficulties

Neuroticism, a broad trait measure of the tendency to experience negative emotions and vulnerability to stress, is consistently related to poor sleep quality. Less is known about potential pleiotropy in the genetic risk for high neuroticism and poor sleep. Therefore, the present study examined whether polygenic score (PGS) for neuroticism is related to sleep quality in two large samples of adults. In addition, depressive symptoms, anxiety and phenotypical neuroticism were tested as mediators in both samples. Participants were 8316 individuals aged from 50 to 101 years (mean age = 68.29, SD = 9.83) from the Health and Retirement Study, and 4973 individuals aged from 63 to 67 years (mean age = 64.30, SD = 0.68) from the Wisconsin Longitudinal Study. Participants from both samples were genotyped and answered questions on sleep quality. A higher PGS for neuroticism was related to lower sleep quality concurrently and over time in both samples. Anxiety, depressive symptoms and neuroticism mediated these relationships in the two samples. Although effect sizes were small, the present study provides replicable evidence that individuals with a higher genetic predisposition to experience negative emotions and distress are at risk of sleep difficulties.

The role of sleep and wakefulness in myelin plasticity

Myelin plasticity is gaining increasing recognition as an essential partner to synaptic plasticity, which mediates experience-dependent brain structure and function. However, how neural activity induces adaptive myelination and which mechanisms are involved remain open questions. More than two decades of transcriptomic studies in rodents have revealed that hundreds of brain transcripts change their expression in relation to the sleep-wake cycle. These studies consistently report upregulation of myelin-related genes during sleep, suggesting that sleep represents a window of opportunity during which myelination occurs. In this review, we summarize recent molecular and morphological studies detailing the dependence of myelin dynamics after sleep, wake, and chronic sleep loss, a condition that can affect myelin substantially. We present novel data about the effects of sleep loss on the node of Ranvier length and provide a hypothetical mechanism through which myelin changes in response to sleep loss. Finally, we discuss the current findings in humans, which appear to confirm the important role of sleep in promoting white matter integrity.

Significant role of gene-gene interactions of clock genes in mood disorder

BACKGROUND

The genetic interactions in the circadian rhythm biological system are promising as a source of pathophysiology in mood disorder. We examined the role of the gene-gene interactions of clock genes in mood disorder.

METHODS

We included 413 patients with mood disorder and 1294 controls. The clock genes investigated were BHLHB2, CLOCK, CSNK1E, NR1D1, PER2, PER3, and TIMELESS. Allele, genotype, and haplotype associations were tested. Gene--gene interactions were analyzed using the non-parametric model-free multifactor-dimensionality reduction (MDR) method.

RESULTS

TIMELESS rs4630333 and CSNK1E rs135745 were significantly associated with both major depressive disorder and bipolar disorder. The CLOCK haplotype was also strongly associated. The genetic roles of these SNPs were consistent from the allele and genotypic associations to the MDR interaction results. In MDR analysis, the combination of TIMELESS rs4630333 and CSNK1E rs135745 exhibited the most significant association with mood disorders in the two-locus model. BHLHB2 rs2137947 for major depressive disorder and CLOCK rs12649507 for bipolar disorder were the most significant third loci in the three-locus combination model. The four-locus SNP combination model showed the best balanced accuracy (BA), but its cross-validation consistency (CVC) was unsatisfactory.

LIMITATIONS

We included only 17 SNPs for seven circadian genes due to our limited resources; all subjects were ethnically Korean.

CONCLUSIONS

Our results suggest significant single-gene associations and gene-gene interactions of circadian genes with mood disorder. Gene-gene interactions play a crucial role in mood disorder, even when individual clock genes do not have significant roles.

Genome-wide DNA methylomic differences between dorsolateral prefrontal and temporal pole cortices of bipolar disorder

Dorsolateral prefrontal cortex (DLPFC) and temporal pole (TP) are brain regions that display abnormalities in bipolar disorder (BD) patients. DNA methylation - an epigenetic mechanism both heritable and sensitive to the environment - may be involved in the pathophysiology of BD. To study BD-associated DNA methylomic differences in these brain regions, we extracted genomic DNA from the postmortem tissues of Brodmann Area (BA) 9 (DLPFC) and BA38 (TP) gray matter from 20 BD, ten major depression (MDD), and ten control age-and-sex-matched subjects. Genome-wide methylation levels were measured using the 850 K Illumina MethylationEPIC BeadChip. We detected striking differences between cortical regions, with greater numbers of between-brain-region differentially methylated positions (DMPs; i.e., CpG sites) in all groups, most pronounced in the BD group, and with substantial overlap across groups. The genes of DMPs common to both BD and MDD (hypothetically associated with their common features such as depression) and those distinct to BD (hypothetically associated with BD-specific features such as mania) were enriched in pathways involved in neurodevelopment including axon guidance. Pathways enriched only in the BD-MDD shared list pointed to GABAergic dysregulation, while those enriched in the BD-only list suggested glutamatergic dysregulation and greater impact on synaptogenesis and synaptic plasticity. We further detected group-specific between-brain-region gene expression differences in ODC1, CALY, GALNT2, and GABRD, which contained significant between-brain-region DMPs. In each brain region, no significant DMPs or differentially methylated regions (DMRs) were found between diagnostic groups. In summary, the methylation differences between DLPFC and TP may provide molecular targets for further investigations of genetic and environmental vulnerabilities associated with both unique and common features of various mood disorders and suggest directions of future development of individualized treatment strategies.

Longitudinal change of sleep timing: association between chronotype and longevity in older adults

Evening-oriented sleep timing preferences have been associated with risk of diabetes, cardiovascular diseases, obesity, psychiatric disorders, and increased mortality. This research aims to explore the relationship between diurnal preferences (chronotype), daily habits, metabolic health, and mortality, using longitudinal data from The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age (6375 participants at inception, recruited in the North of England) with a long follow-up period (up to 35.5 years). Mixed models were used to investigate the influence of aging, socio-demographic, and seasonal factors on sleep timing. Results show that sleep timing shifted towards earlier time with aging. Test seasons influence chronotype of older adults but working schedules challenge seasonality of sleep timing. Moreover, the season of birth may set chronotype in adulthood. Individual chronotype trajectories were clustered using latent class analysis and analyzed against metabolic health and mortality. We observed a higher risk of hypertension in the evening-type cluster compared to morning-type individuals (Odds ratio = 1.88, 95%CI = 1.02/3.47, p = .04). Evening-type cluster was also associated with traits related to lower health such as reduced sport participation, increased risk of depression and psychoticism personality, late eating, and increased smoking and alcohol usage. Finally, Cox regression of proportional hazards was used to study the effects of chronotype on longevity after adjusting for sleep duration, age, gender, smoking, alcohol usage, general health, and social class. The survival analysis (82.6% censored by death) revealed that evening-type chronotype increased the likelihood of mortality (Hazard ratio = 1.15, 95%CI = 1.04/1.26, p = .005). Taken together, chronotype is influenced by aging and seasonal effects. Evening-type preference may have detrimental outcomes for human well-being and longevity.

Genome-wide association study of multisite chronic pain in UK Biobank

Chronic pain is highly prevalent worldwide and represents a significant socioeconomic and public health burden. Several aspects of chronic pain, for example back pain and a severity-related phenotype 'chronic pain grade', have been shown previously to be complex heritable traits with a polygenic component. Additional pain-related phenotypes capturing aspects of an individual's overall sensitivity to experiencing and reporting chronic pain have also been suggested as a focus for investigation. We made use of a measure of the number of sites of chronic pain in individuals within the UK general population. This measure, termed Multisite Chronic Pain (MCP), is a complex trait and its genetic architecture has not previously been investigated. To address this, we carried out a large-scale genome-wide association study (GWAS) of MCP in ~380,000 UK Biobank participants. Our findings were consistent with MCP having a significant polygenic component, with a Single Nucleotide Polymorphism (SNP) heritability of 10.2%. In total 76 independent lead SNPs at 39 risk loci were associated with MCP. Additional gene-level association analyses identified neurogenesis, synaptic plasticity, nervous system development, cell-cycle progression and apoptosis genes as enriched for genetic association with MCP. Genetic correlations were observed between MCP and a range of psychiatric, autoimmune and anthropometric traits, including major depressive disorder (MDD), asthma and Body Mass Index (BMI). Furthermore, in Mendelian randomisation (MR) analyses a causal effect of MCP on MDD was observed. Additionally, a polygenic risk score (PRS) for MCP was found to significantly predict chronic widespread pain (pain all over the body), indicating the existence of genetic variants contributing to both of these pain phenotypes. Overall, our findings support the proposition that chronic pain involves a strong nervous system component with implications for our understanding of the physiology of chronic pain. These discoveries may also inform the future development of novel treatment approaches.

Genetics of Circadian Rhythms

In mammals, genetic influences of circadian rhythms occur at many levels. A set of core "clock genes" have been identified that form a feedback loop of gene transcription and translation. The core genetic clockwork generates circadian rhythms in cells throughout the body. Polymorphisms in both core clock genes and interacting genes contribute to individual differences in the expression and properties of circadian rhythms. The circadian clock profoundly influences the patterns of gene expression and cellular functions, providing a mechanistic basis for the impact of the genetic circadian system on normal physiological processes as well as the development of diseases.

Role of MEIS1 in restless legs syndrome: From GWAS to functional studies in mice

MEIS1 is a transcription factor playing an important role in the development of several organs, including central and peripheral nervous systems. A genetic locus spanning the MEIS1 coding region has been associated with the risk of RLS in genome-wide association studies, with increasing evidence that MEIS1 is the causal RLS gene. The RLS-linked genetic signal has been mapped to an intronic regulatory element within MEIS1. This element plays a role in the ganglionic eminences of the developing forebrain, with the RLS risk allele related to a reduced activation of the enhancer. This suggests that the ganglionic eminences play an important role in the development of genetic susceptibility to RLS. In addition, rare variants within MEIS1 have been shown to contribute to the disease risk. These variants were identified first in RLS families and later found in further RLS cases by targeted sequencing. Some of these variants alone are sufficient to suppress MEIS1 function in neural development, providing further evidence of the importance of neurodevelopmental processes in the pathological mechanism of MEIS1 in RLS. Heterozygous Meis1 inactivation in mice causes hyperactivity at the onset of the inactive period, consistent with human RLS. In addition, these mice revealed an effect of MEIS1 on the dopaminergic system at both the spinal and supraspinal level. More studies are needed in human genetics to determine the exact role of MEIS1 variants in the risk of RLS, as well as in functional genetics and animal studies to further elucidate the pathological mechanism of MEIS1 in RLS.

Missing a beat: assessment of circadian rhythm abnormalities in bipolar disorder in the genomic era

Circadian rhythm abnormalities have been recognized as a central feature of bipolar disorder (BD) but a coherent biological explanation for them remains lacking. Using genetic mutation of 'clock genes', robust animal models of mania and depression have been developed that elucidate key aspects of circadian rhythms and the circadian clock-mood connection. However, translation of this knowledge into humans remains incomplete. In recent years, very large genome-wide association studies (GWAS) have been conducted and the genetic underpinnings of BD are beginning to emerge. However, these genetic studies in BD do not match well with the evidence from animal studies that implicate the circadian clock in mood regulation. Even larger GWAS have been conducted for circadian phenotypes including chronotype, rhythm amplitude, sleep duration, and insomnia. These studies have identified a diverse set of associated genes, including a minority with previously well-characterized functions in the circadian clock. Taken together, the data from recent GWAS of BD and circadian phenotypes indicate that the genetic organization of the circadian clock, both in health and in BD is complex. The findings from GWAS elucidate potentially novel circadian mechanism that may be partly distinct from those identified in animal models. Pleiotropy, epistasis and nongenetic factors may play important roles in regulating circadian rhythms, some of which may underlie circadian rhythm disturbances in BD.