Genetic risk factors for schizophrenia associate with sleep spindle activity in healthy adolescents

A Thalamocortical Perspective on Sleep Spindle Alterations in Neurodevelopmental Disorders

Purpose of Review

Neurodevelopmental disorders are a group of conditions that affect the development and function of the nervous system, typically arising early in life. These disorders can have various genetic, environmental, and/or neural underpinnings, which can impact the thalamocortical system. Sleep spindles, brief bursts of oscillatory activity that occur during NREM sleep, provide a unique in vivo measure of the thalamocortical system. In this manuscript, we review the development of the thalamocortical system and sleep spindles in rodent models and humans. We then utilize this as a foundation to discuss alterations in sleep spindle activity in four of the most pervasive neurodevelopmental disorders-intellectual disability, attention deficit hyperactivity disorder, autism, and schizophrenia.

Recent Findings

Recent work in humans has shown alterations in sleep spindles across several neurodevelopmental disorders. Simultaneously, rodent models have elucidated the mechanisms which may underlie these deficits in spindle activity. This review merges recent findings from these two separate lines of research to draw conclusions about the pathogenesis of neurodevelopmental disorders.

Summary

We speculate that deficits in the thalamocortical system associated with neurodevelopmental disorders are exquisitely reflected in sleep spindle activity. We propose that sleep spindles may represent a promising biomarker for drug discovery, risk stratification, and treatment monitoring.

Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis

BACKGROUND AND HYPOTHESIS

Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes.

STUDY DESIGN

We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score.

STUDY RESULTS

After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores.

CONCLUSIONS

Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

How Machine Learning is Powering Neuroimaging to Improve Brain Health

This report presents an overview of how machine learning is rapidly advancing clinical translational imaging in ways that will aid in the early detection, prediction, and treatment of diseases that threaten brain health. Towards this goal, we aresharing the information presented at a symposium, "Neuroimaging Indicators of Brain Structure and Function - Closing the Gap Between Research and Clinical Application", co-hosted by the McCance Center for Brain Health at Mass General Hospital and the MIT HST Neuroimaging Training Program on February 12, 2021. The symposium focused on the potential for machine learning approaches, applied to increasingly large-scale neuroimaging datasets, to transform healthcare delivery and change the trajectory of brain health by addressing brain care earlier in the lifespan. While not exhaustive, this overview uniquely addresses many of the technical challenges from image formation, to analysis and visualization, to synthesis and incorporation into the clinical workflow. Some of the ethical challenges inherent to this work are also explored, as are some of the regulatory requirements for implementation. We seek to educate, motivate, and inspire graduate students, postdoctoral fellows, and early career investigators to contribute to a future where neuroimaging meaningfully contributes to the maintenance of brain health.

Sleep EEG in young people with 22q11.2 deletion syndrome: A cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms

Background

Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions.

Methods

In a cross-sectional design, we recorded high-density sleep EEG in young people (6-20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep.

Results

22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures.

Conclusions

This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders.

Funding

This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award 'Defining Endophenotypes From Integrated Neurosciences' Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders.

Topographical relocation of adolescent sleep spindles reveals a new maturational pattern in the human brain

Current theories of human neural development emphasize the posterior-to-anterior pattern of brain maturation. However, this scenario leaves out significant brain areas not directly involved with sensory input and behavioral control. Suggesting the relevance of cortical activity unrelated to sensory stimulation, such as sleep, we investigated adolescent transformations in the topography of sleep spindles. Sleep spindles are known to be involved in neural plasticity and in adults have a bimodal topography: slow spindles are frontally dominant, while fast spindles have a parietal/precuneal origin. The late functional segregation of the precuneus from the frontoparietal network during adolescence suggests that spindle topography might approach the adult state relatively late in development, and it may not be a result of the posterior-to-anterior maturational pattern. We analyzed the topographical distribution of spindle parameters in HD-EEG polysomnographic sleep recordings of adolescents and found that slow spindle duration maxima traveled from central to anterior brain regions, while fast spindle density, amplitude and frequency peaks traveled from central to more posterior brain regions. These results provide evidence for the gradual posteriorization of the anatomical localization of fast sleep spindles during adolescence and indicate the existence of an anterior-to-posterior pattern of human brain maturation.

Association of polygenic risk for schizophrenia with fast sleep spindle density depends on pro-cognitive variants

Cognitive impairment is a common feature in schizophrenia and the strongest prognostic factor for long-term outcome. Identifying a trait associated with the genetic background for cognitive outcome in schizophrenia may aid in a deeper understanding of clinical disease subtypes. Fast sleep spindles may represent such a biomarker as they are strongly genetically determined, associated with cognitive functioning and impaired in schizophrenia and unaffected relatives. We measured fast sleep spindle density in 150 healthy adults and investigated its association with a genome-wide polygenic score for schizophrenia (SCZ-PGS). The association between SCZ-PGS and fast spindle density was further characterized by stratifying it to the genetic background of intelligence. SCZ-PGS was positively associated with fast spindle density. This association mainly depended on pro-cognitive genetic variants. Our results strengthen the evidence for a genetic background of spindle abnormalities in schizophrenia. Spindle density might represent an easily accessible marker for a favourable cognitive outcome which should be further investigated in clinical samples.

Schizophrenia-associated variation at ZNF804A correlates with altered experience-dependent dynamics of sleep slow waves and spindles in healthy young adults

The rs1344706 polymorphism in ZNF804A is robustly associated with schizophrenia and schizophrenia is, in turn, associated with abnormal non-rapid eye movement (NREM) sleep neurophysiology. To examine whether rs1344706 is associated with intermediate neurophysiological traits in the absence of disease, we assessed the relationship between genotype, sleep neurophysiology, and sleep-dependent memory consolidation in healthy participants. We recruited healthy adult males with no history of psychiatric disorder from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Participants were homozygous for either the schizophrenia-associated 'A' allele (N = 22) or the alternative 'C' allele (N = 18) at rs1344706. Actigraphy, polysomnography (PSG) and a motor sequence task (MST) were used to characterize daily activity patterns, sleep neurophysiology and sleep-dependent memory consolidation. Average MST learning and sleep-dependent performance improvements were similar across genotype groups, albeit more variable in the AA group. During sleep after learning, CC participants showed increased slow-wave (SW) and spindle amplitudes, plus augmented coupling of SW activity across recording electrodes. SW and spindles in those with the AA genotype were insensitive to learning, whilst SW coherence decreased following MST training. Accordingly, NREM neurophysiology robustly predicted the degree of overnight motor memory consolidation in CC carriers, but not in AA carriers. We describe evidence that rs1344706 polymorphism in ZNF804A is associated with changes in the coordinated neural network activity that supports offline information processing during sleep in a healthy population. These findings highlight the utility of sleep neurophysiology in mapping the impacts of schizophrenia-associated common genetic variants on neural circuit oscillations and function.

Sleep in first-episode schizophrenia patients, their unaffected siblings and healthy controls: A comparison

BACKGROUND

Sleep disturbances in schizophrenia are common throughout its course including in the prodrome, and have been mainly attributed to severity of symptoms and antipsychotic use. We aimed to investigate whether early course patients with schizophrenia and young non-psychotic siblings of patients with schizophrenia also show sleep disturbances and whether sleep correlates with symptoms and functioning.

METHODS

Three study groups, that is, adults newly diagnosed with schizophrenia (n = 54), young non-psychotic siblings of schizophrenia patients (n = 56) and a sample of healthy controls matched to the patients and siblings (n = 61) were evaluated on Horne and Ostberg Morningness-Eveningness Questionnaire, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index. Severity of symptoms and functioning are assessed using the Positive and Negative Syndrome Scale and the Global Assessment of Functioning Scale, respectively. Age, gender, occupation and marital status were regarded as covariates, and differences between the three groups were evaluated using analysis of covariance.

RESULTS

Early course schizophrenia patients and non-psychotic siblings of schizophrenia patients showed significantly reduced sleep quality relative to healthy controls (P < .001). Schizophrenia patients had significantly higher daytime sleepiness compared to controls (P < .001). Chronotypes in schizophrenia patients and unaffected siblings did not significantly differ from those of the healthy controls.

CONCLUSIONS

Like chronic medicated schizophrenia patients, early course schizophrenia patients and young non-psychotic siblings of individuals with schizophrenia have sleep disturbances. These findings indicate that sleep markers can distinguish unaffected siblings of schizophrenia from healthy controls and serve as an endophenotype for schizophrenia.

Sleep and Memory Consolidation Dysfunction in Psychiatric Disorders: Evidence for the Involvement of Extracellular Matrix Molecules

Sleep disturbances and memory dysfunction are key characteristics across psychiatric disorders. Recent advances have revealed insight into the role of sleep in memory consolidation, pointing to key overlap between memory consolidation processes and structural and molecular abnormalities in psychiatric disorders. Ongoing research regarding the molecular mechanisms involved in memory consolidation has the potential to identify therapeutic targets for memory dysfunction in psychiatric disorders and aging. Recent evidence from our group and others points to extracellular matrix molecules, including chondroitin sulfate proteoglycans and their endogenous proteases, as molecules that may underlie synaptic dysfunction in psychiatric disorders and memory consolidation during sleep. These molecules may provide a therapeutic targets for decreasing strength of reward memories in addiction and traumatic memories in PTSD, as well as restoring deficits in memory consolidation in schizophrenia and aging. We review the evidence for sleep and memory consolidation dysfunction in psychiatric disorders and aging in the context of current evidence pointing to the involvement of extracellular matrix molecules in these processes.

Polygenic impact of morningness on the overnight dynamics of sleep spindle amplitude

Sleep spindles are thalamocortical oscillations that contribute to sleep maintenance and sleep-related brain plasticity. The current study is an explorative study of the circadian dynamics of sleep spindles in relation to a polygenic score (PGS) for circadian preference towards morningness. The participants represent the 17-year follow-up of a birth cohort having both genome-wide data and an ambulatory sleep electroencephalography measurement available ( N = 154, Mean age = 16.9, SD = 0.1 years, 57% girls). Based on a recent genome-wide association study, we calculated a PGS for circadian preference towards morningness across the whole genome, including 354 single-nucleotide polymorphisms. Stage 2 slow (9-12.5 Hz, N = 186 739) and fast (12.5-16 Hz, N = 135 504) sleep spindles were detected using an automated algorithm with individual time tags and amplitudes for each spindle. There was a significant interaction of PGS for morningness and timing of sleep spindles across the night. These growth curve models showed a curvilinear trajectory of spindle amplitudes: those with a higher PGS for morningness showed higher slow spindle amplitudes in frontal derivations, and a faster dissipation of spindle amplitude in central derivations. Overall, the findings provide new evidence on how individual sleep spindle trajectories are influenced by genetic factors associated with circadian type. The finding may lead to new hypotheses on the associations previously observed between circadian types, psychiatric problems and spindle activity.

Sleep disturbances in schizophrenia: what we know, what still needs to be done

Sleep disturbances are commonly observed in schizophrenia (SCZ) and are associated with worse psychotic symptoms and poorer clinical outcomes. Early polysomnography studies have focused on characterizing differences in sleep architecture between patients with SCZ and healthy controls. More recently, research has focused on sleep-specific EEG oscillations, such as sleep spindles and slow waves, which reflect the integrity of underlying thalamo-cortical networks. Furthermore, high-density (hd)-EEG (≥64 channels), which affords enhanced spatial resolution, has been employed to better localize abnormalities in sleep characteristics and related thalamo-cortical circuits in patients with SCZ and related disorders. In this article, we will review the most relevant sleep abnormalities reported in SCZ, with an emphasis on recent findings, and propose directions for future research.

Genetic Associations between Voltage-Gated Calcium Channels and Psychiatric Disorders

Psychiatric disorders are mental, behavioral or emotional disorders. These conditions are prevalent, one in four adults suffer from any type of psychiatric disorders world-wide. It has always been observed that psychiatric disorders have a genetic component, however, new methods to sequence full genomes of large cohorts have identified with high precision genetic risk loci for these conditions. Psychiatric disorders include, but are not limited to, bipolar disorder, schizophrenia, autism spectrum disorder, anxiety disorders, major depressive disorder, and attention-deficit and hyperactivity disorder. Several risk loci for psychiatric disorders fall within genes that encode for voltage-gated calcium channels (CaVs). Calcium entering through CaVs is crucial for multiple neuronal processes. In this review, we will summarize recent findings that link CaVs and their auxiliary subunits to psychiatric disorders. First, we will provide a general overview of CaVs structure, classification, function, expression and pharmacology. Next, we will summarize tools to study risk loci associated with psychiatric disorders. We will examine functional studies of risk variations in CaV genes when available. Finally, we will review pharmacological evidence of the use of CaV modulators to treat psychiatric disorders. Our review will be of interest for those studying pathophysiological aspects of CaVs.

Autistic Traits Are Associated With Decreased Activity of Fast Sleep Spindles During Adolescence

STUDY OBJECTIVES

Autistic traits present a continuum from mild symptoms to severe disorder and have been associated with a high prevalence of sleep problems. Sleep spindles have a key function in sleep maintenance and in brain plasticity. Previous studies have found decreased spindle activity in clinical autism. Here we examine the associations between the entire range of autistic traits and sleep spindle activity in a nonclinical community cohort of adolescents.

METHODS

Our cohort is based on 172 adolescents born in 1998 (58.7% girls, mean age = 16.9 years, standard deviation = 0.1), who filled in the adult autism-spectrum quotient (AQ), consisting of total score, and social interaction and attention to details subscales. Participants underwent an ambulatory overnight sleep electroencephalography. Sleep spindles (amplitude, duration, density, and intensity) were automatically detected from stage N2 sleep, and divided to slow and fast spindles.

RESULTS

Higher AQ total sum and social interaction sum associated with lower fast spindle amplitude and intensity (P < .04). No associations were observed for attention to details.

CONCLUSIONS

Our findings indicate that a higher level of autistic traits in the nonclinical range among generally healthy adolescents associate with similar alterations in sleep spindle activity as observed in many neuropsychiatric conditions, indicating lower sleep-related brain plasticity. This indicates that sleep microstructures form a continuum that follows self-reported symptoms of autism.