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

Age-Related Changes in Sleep and Its Implications for Cognitive Decline in Aging Persons With Schizophrenia: A Critical Review

BACKGROUND AND HYPOTHESIS

Cognitive impairment is a core feature of schizophrenia that worsens with aging and interferes with quality of life. Recent work identifies sleep as an actionable target to alleviate cognitive deficits. Cardinal non-rapid eye movement (NREM) sleep oscillations such as sleep spindles and slow oscillations are critical for cognition. People living with schizophrenia (PLWS) and their first-degree relatives have a specific reduction in sleep spindles and an abnormality in their temporal coordination with slow oscillations that predict impaired memory consolidation. While NREM oscillatory activity is reduced in typical aging, it is not known how further disruption in these oscillations contributes to cognitive decline in older PLWS. Another understudied risk factor for cognitive deficits among older PLWS is obstructive sleep apnea (OSA) which may contribute to cognitive decline.

STUDY DESIGN

We conducted a narrative review to examine the published literature on aging, OSA, and NREM sleep oscillations in PLWS.

STUDY RESULTS

Spindles are propagated via thalamocortical feedback loops, and this circuitry shows abnormal hyperconnectivity in schizophrenia as revealed by structural and functional MRI studies. While the risk and severity of OSA increase with age, older PLWS are particularly vulnerable to OSA-related cognitive deficits because OSA is often underdiagnosed and undertreated, and OSA adds further damage to the circuitry that generates NREM sleep oscillations.

CONCLUSIONS

We highlight the critical need to study NREM sleep in older PWLS and propose that identifying and treating OSA in older PLWS will provide an avenue to potentially mitigate and prevent cognitive decline.

The objective assessment of sleep in cluster headache: State of the art and future directions

Several lines of evidence suggest that cluster headache is related to chronobiology and sleep. Nevertheless, the nature of such a relationship is unclear. In this view, the objective evaluation of sleep in cluster headache has strong theoretical and clinical relevance. Here, we provide an in-depth narrative review of the literature on objective sleep assessment in cluster headache. We found that only a small number of studies (N = 12) focused on this topic. The key research aims were directed to assess: (a) the relationship between cluster headache and sleep breathing disorders; (b) the temporal relationship between sleep stages/events and cluster headache attacks; (c) sleep macrostructure in patients with cluster headache. No studies considered sleep microstructure. The reviewed studies are heterogeneous, conducted by a few research groups, and often characterised by relevant methodological flaws. Results are substantially inconclusive considering the main hypothesis. We outline several methodological points that should be considered for future research, and suggest that evaluating sleep microstructure, local sleep electrophysiology and actigraphic measures may strongly increase knowledge on the relationship between sleep and cluster headache.

A spectrum of altered non-rapid eye movement sleep in schizophrenia

Background

Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations (SO), are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses which treat all patients as a unitary set, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, illness duration and ageing, cognitive profiles and medication regimens. Using newly collected high density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported (Kozhemiako et. al, 2022) group-level mean differences between patients and controls (original N=130). Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability in NREM neurophysiology.

Results

We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (Area Under the ROC Curve, AUC = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics, with patterns only partially recapitulating those for group-level mean differences. Although multiple clinical and cognitive factors were associated with NREM metrics including spindle density, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater (albeit still partial) contributor to variability, although original group mean differences persisted after controlling for medications. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on an independent model of ageing and the sleep EEG.

Conclusion

We demonstrated robust and replicable alterations in sleep neurophysiology in individuals with SCZ and highlighted distinct patterns of effects contrasting between-group means versus within-group variances. We further documented and controlled for a major effect of medication use, and pointed to greater age-related change in NREM sleep in patients. That increased NREM heterogeneity was not explained by standard clinical or cognitive patient assessments suggests the sleep EEG provides novel, nonredundant information to support the goals of personalized medicine. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ patients that can be measured objectively and at scale, and that may offer a unique window on the etiological and genetic diversity that underlies SCZ risk, treatment response and prognosis.

Performance evaluation of metaheuristics-tuned recurrent neural networks for electroencephalography anomaly detection

Electroencephalography (EEG) serves as a diagnostic technique for measuring brain waves and brain activity. Despite its precision in capturing brain electrical activity, certain factors like environmental influences during the test can affect the objectivity and accuracy of EEG interpretations. Challenges associated with interpretation, even with advanced techniques to minimize artifact influences, can significantly impact the accurate interpretation of EEG findings. To address this issue, artificial intelligence (AI) has been utilized in this study to analyze anomalies in EEG signals for epilepsy detection. Recurrent neural networks (RNNs) are AI techniques specifically designed to handle sequential data, making them well-suited for precise time-series tasks. While AI methods, including RNNs and artificial neural networks (ANNs), hold great promise, their effectiveness heavily relies on the initial values assigned to hyperparameters, which are crucial for their performance for concrete assignment. To tune RNN performance, the selection of hyperparameters is approached as a typical optimization problem, and metaheuristic algorithms are employed to further enhance the process. The modified hybrid sine cosine algorithm has been developed and used to further improve hyperparameter optimization. To facilitate testing, publicly available real-world EEG data is utilized. A dataset is constructed using captured data from healthy and archived data from patients confirmed to be affected by epilepsy, as well as data captured during an active seizure. Two experiments have been conducted using generated dataset. In the first experiment, models were tasked with the detection of anomalous EEG activity. The second experiment required models to segment normal, anomalous activity as well as detect occurrences of seizures from EEG data. Considering the modest sample size (one second of data, 158 data points) used for classification models demonstrated decent outcomes. Obtained outcomes are compared with those generated by other cutting-edge metaheuristics and rigid statistical validation, as well as results' interpretation is performed.

Multivariate patterns of disrupted sleep longitudinally predict affective vulnerability to psychosis in 22q11.2 Deletion Syndrome

22q11.2 deletion syndrome (22q11DS) contributes dramatically to increased genetic risk for psychopathology, and in particular schizophrenia. Sleep disorders, including obstructive sleep apnea (OSA), are also highly prevalent, making 22q11DS a unique model to explore their impact on psychosis vulnerability. Still, the contribution of sleep disturbances to psychosis vulnerability remains unclear. We characterized the sleep phenotype of 69 individuals with 22q11DS and 38 healthy controls with actigraphy and sleep questionnaires. Psychiatric symptoms were measured concomitantly with the baseline sleep assessment and at longitudinal follow-up, 3.58±0.85 years later. We used a novel multivariate partial-least-square-correlation (PLSC) approach to identify sleep patterns combining objective and subjective variables, which correlated with psychiatric symptoms. We dissected longitudinal pathways linking sleep disturbances to psychosis, using multi-layer-network-analysis. 22q11DS was characterized by a non-restorative sleep pattern, combining increased daytime fatigue despite longer sleep duration. Non-restorative sleep combined with OSA symptoms correlated with both emotional and psychotic symptoms. Moreover, a sleep pattern evocative of OSA predicted longitudinal worsening of positive and negative symptoms, by accentuating the effects of emotional dysregulation. These results suggest that sleep disturbances could significantly increase psychosis risk, along an affective pathway. If confirmed, this suggests that systematic screening of sleep quality could mitigate psychosis vulnerability in 22q11DS.

The Feature of Sleep Spindle Deficits in Patients With Schizophrenia With and Without Auditory Verbal Hallucinations

BACKGROUND

Previous sleep electroencephalography studies have detected abnormalities in sleep architecture and sleep spindle deficits in schizophrenia (SCZ), but the consistency of these results was not robust, which might be due to the small sample size and the influence of clinical factors such as the various medication therapies and symptom heterogeneity. This study aimed to regard auditory verbal hallucinations (AVHs) as a pointcut to downscale the heterogeneity of SCZ and explore whether some sleep architecture and spindle parameters were more severely impaired in SCZ patients with AVHs compared with those without AVHs.

METHODS

A total of 90 SCZ patients with AVHs, 92 SCZ patients without AVHs, and 91 healthy control subjects were recruited, and parameters of sleep architecture and spindle activities were compared between groups. The correlation between significant sleep parameters and clinical indicators was analyzed.

RESULTS

Deficits of sleep spindle activities at prefrontal electrodes and intrahemispheric spindle coherence were observed in both AVH and non-AVH groups, several of which were more serious in the AVH group. In addition, deficits of spindle activities at central and occipital electrodes and interhemispheric spindle coherence mainly manifested accompanying AVH symptoms, most of which were retained in the medication-naive first-episode patients, and were associated with Auditory Hallucination Rating Scale scores.

CONCLUSIONS

Our results suggest that the underlying mechanism of spindle deficits might be different between SCZ patients with and without AVHs. In the future, the sleep feature of SCZ patients with different symptoms and the influence of clinical factors, such as medication therapy, should be further illustrated.

Association of daytime napping frequency and schizophrenia: a bidirectional two-sample Mendelian randomization study

BACKGROUND

The bidirectional causal association between daytime napping frequency and schizophrenia is unclear.

METHODS

A bidirectional two-sample Mendelian randomization (MR) analysis was conducted with summary statistics of top genetic variants associated with daytime napping frequency and schizophrenia from genome-wide association studies (GWAS). The single nucleotide polymorphisms (SNPs) data of daytime napping frequency GWAS came from the UK Biobank (n = 452,633) and 23andMe study cohort (n = 541,333), while the schizophrenia GWAS came from the Psychiatric Genomics Consortium (PGC, 36,989 cases and 113,075 controls). The inverse variance weighted (IVW) analysis was the primary method, with the weighted median, MR-Robust Adjusted Profile Score (RAPS), Radial MR and MR-Pleiotropy Residual Sum Outlier (PRESSO) as sensitivity analysis.

RESULTS

The MR analysis showed a bidirectional causal relationship between more frequent daytime napping and the occurrence of schizophrenia, with the odds ratio (OR) for one-unit increase in napping category (never, sometimes, usually) on schizophrenia was 3.38 (95% confidence interval [CI]: 2.02-5.65, P = 3.58 × 10^-6), and the beta for the occurrence of schizophrenia on daytime napping frequency was 0.0112 (95%CI: 0.0060-0.0163, P = 2.04 × 10^-5). The sensitivity analysis obtained the same conclusions.

CONCLUSION

Our findings support the bidirectional causal association between more daytime napping frequency and schizophrenia, implying that daytime napping frequency is a potential intervention for the progression and treatment of schizophrenia.

Alterations in TRN-anterodorsal thalamocortical circuits affect sleep architecture and homeostatic processes in oxidative stress vulnerable Gclm-/- mice

Schizophrenia is associated with alterations of sensory integration, cognitive processing and both sleep architecture and sleep oscillations in mouse models and human subjects, possibly through changes in thalamocortical dynamics. Oxidative stress (OxS) damage, including inflammation and the impairment of fast-spiking gamma-aminobutyric acid neurons have been hypothesized as a potential mechanism responsible for the onset and development of schizophrenia. Yet, the link between OxS and perturbation of thalamocortical dynamics and sleep remains unclear. Here, we sought to investigate the effects of OxS on sleep regulation by characterizing the dynamics of thalamocortical networks across sleep-wake states in a mouse model with a genetic deletion of the modifier subunit of glutamate-cysteine ligase (Gclm knockout, KO) using high-density electrophysiology in freely-moving mice. We found that Gcml KO mice exhibited a fragmented sleep architecture and impaired sleep homeostasis responses as revealed by the increased NREM sleep latencies, decreased slow-wave activities and spindle rate after sleep deprivation. These changes were associated with altered bursting activity and firing dynamics of neurons from the thalamic reticularis nucleus, anterior cingulate and anterodorsal thalamus. Administration of N-acetylcysteine (NAC), a clinically relevant antioxidant, rescued the sleep fragmentation and spindle rate through a renormalization of local neuronal dynamics in Gclm KO mice. Collectively, these findings provide novel evidence for a link between OxS and the deficits of frontal TC network dynamics as a possible mechanism underlying sleep abnormalities and impaired homeostatic responses observed in schizophrenia.

Altered circadian activity and sleep/wake rhythms in the stable tubule only polypeptide (STOP) null mouse model of schizophrenia

Sleep and circadian rhythm disruptions commonly occur in individuals with schizophrenia. Stable tubule only polypeptide (STOP) knockout (KO) mice show behavioral impairments resembling symptoms of schizophrenia. We previously reported that STOP KO mice slept less and had more fragmented sleep and waking than wild-type littermates under a light/dark (LD) cycle. Here, we assessed the circadian phenotype of male STOP KO mice by examining wheel-running activity rhythms and EEG/EMG-defined sleep/wake states under both LD and constant darkness (DD) conditions. Wheel-running activity rhythms in KO and wild-type mice were similarly entrained in LD, and had similar free-running periods in DD. The phase delay shift in response to a light pulse given early in the active phase under DD was preserved in KO mice. KO mice had markedly lower activity levels, lower amplitude activity rhythms, less stable activity onsets, and more fragmented activity than wild-type mice in both lighting conditions. KO mice also spent more time awake and less time in rapid eye movement sleep (REMS) and non-REMS (NREMS) in both LD and DD conditions, with the decrease in NREMS concentrated in the active phase. KO mice also showed altered EEG features and higher amplitude rhythms in wake and NREMS (but not REMS) amounts in both lighting conditions, with a longer free-running period in DD, compared to wild-type mice. These results indicate that the STOP null mutation in mice altered the regulation of sleep/wake physiology and activity rhythm expression, but did not grossly disrupt circadian mechanisms.

Association of neurocognitive functioning with sleep stage dissociation and REM sleep instability in medicated patients with schizophrenia

Many patients with schizophrenia present with impaired cognitive functioning and sleep disturbances. Dissociated stages of sleep represent instability within distinct sleep regulatory cerebral networks. Previous studies found increased rates of rapid eye movement (REM) sleep abnormalities in patients with schizophrenia and a positive association with psychopathology. In this study, we examined if sleep stage dissociation and REM sleep instability was associated with neurocognitive functioning in a sample of medicated patients with schizophrenia. The analyses were performed on 31 baseline polysomnographic recordings as well as baseline data on neurocognitive performance. Regression models were built with the cognitive composite score as primary dependent variable and measures of sleep stage dissociation, including REM sleep without atonia (RSWA), REM sleep without eye movements, non-REM sleep with eye movements, REM sleep percentage in REM periods and REM sleep stability as independent variables. Analyses were adjusted for age, gender, total antipsychotic dose, total benzodiazepine dose, and symptom severity. After correction for multiple testing, we found that the neurocognitive composite score was inversely associated with the degree of RSWA. Exploratory analyses with the cognitive sub scores as dependent variables showed that RSWA was associated with cognitive performance across several sub domains. Dissociated sleep stages, specifically the RSWA feature, might represent a new treatment target for improving cognitive impairment in patients with schizophrenia.

Increased stem cell proliferation in atherosclerosis accelerates clonal hematopoiesis

Clonal hematopoiesis, a condition in which individual hematopoietic stem cell clones generate a disproportionate fraction of blood leukocytes, correlates with higher risk for cardiovascular disease. The mechanisms behind this association are incompletely understood. Here, we show that hematopoietic stem cell division rates are increased in mice and humans with atherosclerosis. Mathematical analysis demonstrates that increased stem cell proliferation expedites somatic evolution and expansion of clones with driver mutations. The experimentally determined division rate elevation in atherosclerosis patients is sufficient to produce a 3.5-fold increased risk of clonal hematopoiesis by age 70. We confirm the accuracy of our theoretical framework in mouse models of atherosclerosis and sleep fragmentation by showing that expansion of competitively transplanted Tet2^-/- cells is accelerated under conditions of chronically elevated hematopoietic activity. Hence, increased hematopoietic stem cell proliferation is an important factor contributing to the association between cardiovascular disease and clonal hematopoiesis.

A set of composite, non-redundant EEG measures of NREM sleep based on the power law scaling of the Fourier spectrum

Features of sleep were shown to reflect aging, typical sex differences and cognitive abilities of humans. However, these measures are characterized by redundancy and arbitrariness. Our present approach relies on the assumptions that the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram (EEG) during non-rapid eye movement (NREM) sleep is characterized by arrhythmic, scale-free properties and is based on the power law scaling of the Fourier spectra with the additional consideration of the rhythmic, oscillatory waves at specific frequencies, including sleep spindles. Measures derived are the spectral intercept and slope, as well as the maximal spectral peak amplitude and frequency in the sleep spindle range, effectively reducing 191 spectral measures to 4, which were efficient in characterizing known age-effects, sex-differences and cognitive correlates of sleep EEG. Future clinical and basic studies are supposed to be significantly empowered by the efficient data reduction provided by our approach.

Sleep Disturbances in Patients with Persistent Delusions: Prevalence, Clinical Associations, and Therapeutic Strategies

Sleep disturbances accompany almost all mental illnesses, either because sound sleep and mental well-being share similar requisites, or because mental problems lead to sleep problems, or vice versa. The aim of this narrative review was to examine sleep in patients with delusions, particularly in those diagnosed with delusional disorder. We did this in sequence, first for psychiatric illness in general, then for psychotic illnesses where delusions are prevalent symptoms, and then for delusional disorder. The review also looked at the effect on sleep parameters of individual symptoms commonly seen in delusional disorder (paranoia, cognitive distortions, suicidal thoughts) and searched the evidence base for indications of antipsychotic drug effects on sleep. It subsequently evaluated the influence of sleep therapies on psychotic symptoms, particularly delusions. The review’s findings are clinically important. Delusional symptoms and sleep quality influence one another reciprocally. Effective treatment of sleep problems is of potential benefit to patients with persistent delusions, but may be difficult to implement in the absence of an established therapeutic relationship and an appropriate pharmacologic regimen. As one symptom can aggravate another, comorbidities in patients with serious mental illness all need to be treated, a task that requires close liaison among medical specialties.

Assessment of the efficacy of a fatigue management therapy in schizophrenia: study protocol for a randomized, controlled multi-centered study (ENERGY)

Background

Fatigue is a well-known common clinical feature of numerous chronic diseases including various forms of cancer, neurological disorders such as multiple sclerosis, and psychiatric disorders. A significant proportion of people with schizophrenia (30–60%) reportedly experience fatigue, which impacts negatively on participation in various activities, including work, study, leisure, and social pursuits. Causes of fatigue in schizophrenia are poorly understood and there are no established treatments. Several evidence-based interventions for fatigue syndrome including psychoeducation, cognitive behavioral therapy, and graded exercise therapy have been shown to be effective in other medical conditions and could be adapted to address fatigue in schizophrenia patients. As there are no psychosocial or pharmacological interventions with proved efficacy for fatigue in schizophrenia, there is an urgent need for the development of strategies to improve fatigue management in schizophrenia.

The aim of this project is to evaluate in a single blind randomized clinical trial the efficacy of a cognitive-behavioral therapy (CBT) intervention compared to treatment as usual (TAU) on fatigue as the main outcome in schizophrenia patients. Clinical symptoms, physical functioning, major cognitive functions, quality of life and functioning, treatment dosage, daily motor activity, biological markers with inflammatory markers are also considered as secondary outcomes.

Methods/design

Two hundred patients meeting the inclusion criteria will be randomized to either of the study arms (intervention or TAU). The ENERGY intervention will be delivered according to a standardized treatment manual comprising six modules addressing fatigue and sleep over 14 individual therapy sessions. The treatment encompasses core CBT principles of psycho-education, behavioral activation, behavioral experiments, cognitive restructuring, problem-solving, and relapse prevention. Sessions will follow the traditional CBT structure of agenda setting, review of homework tasks, and introduction of a new concept/technique with collaborative discussions on how to implement such strategies in the participant’s day-to-day environment. Our primary endpoint will be the severity of fatigue assessed at baseline and at the 9-month follow-up using the “Multidimensional Fatigue Inventory” (MFI).

Discussion

The trial will provide the first test of CBT intervention for fatigue for patients with schizophrenia. This study will also test to what extent the treatment can be implemented in everyday practice.

Trial registration

ClinicalTrials.govNCT04332601. Registered on 10 April 2020.

Slow wave oscillations in Schizophrenia First-Degree Relatives: A confirmatory analysis and feasibility study on slow wave traveling

Abnormal sleep oscillations have recently been proposed as endophenotypes of schizophrenia. However, optimization of methodological approaches is still necessary to standardize analyses of their microstructural characteristics. Additionally, some relevant features of these oscillations remain unexplored in pathological conditions. Among others, slow wave traveling is a promising proxy for diurnal processes of brain connectivity and excitability. The study of slow oscillations propagation appears particularly relevant when schizophrenia is conceptualized as a dys-connectivity syndrome. Given the rising knowledge on the neurobiological mechanisms underlying slow wave traveling, this measure might offer substantial advantages over other approaches in investigating brain connectivity. Herein we: 1) confirm the stability of our previous findings on slow waves and sleep spindles in FDRs using different automated algorithms, and 2) report the dynamics of slow wave traveling in FDRs of Schizophrenia patients. A 256-channel, high-density EEG system was employed to record a whole night of sleep of 16 FDRs and 16 age- and gender-matched control subjects. A recently developed, open source toolbox was used for slow wave visualization and detection. Slow waves were confirmed to be significantly smaller in FDRs compared to the control group. Additionally, several traveling parameters were analyzed. Traveled distances were found to be significantly reduced in FDRs, whereas origins showed a different topographical pattern of distribution from control subjects. In contrast, local speed did not differ between groups. Overall, these results suggest that slow wave traveling might be a viable method to study pathological conditions interfering with brain connectivity.

Neuromodulation of sleep rhythms in schizophrenia: Towards the rational design of non-invasive brain stimulation

Brain function critically depends on oscillatory synchronization of neuronal populations both during wake and sleep. Originally, neural oscillations have been discounted as an epiphenomenon. More recently, specific deficits in the structure of brain oscillations have been linked to psychiatric diseases. For example, schizophrenia is hallmarked by abnormalities in different brain oscillations. Key sleep rhythms during NEM sleep such as sleep spindles, which are implicated in memory consolidation and are related to cognitive functions, are strongly diminished in these patients compared to healthy controls. To date, it remains unclear whether these reductions in sleep oscillations are causal for the functional impairments observed in schizophrenia. The application of non-invasive brain stimulation permits the causal examination of brain network dynamics and will help to establish the causal association of sleep oscillations and symptoms of schizophrenia. To accomplish this, stimulation paradigms that selectively engage specific network targets such as sleep spindles or slow waves are needed. We propose that the successful development and application of these non-invasive brain stimulation approaches will require rational design that takes network dynamics and neuroanatomical information into account. The purpose of this article is to prepare the grounds for the next steps towards such rational design of non-invasive stimulation, with a special focus on electrical and auditory stimulation. First, we briefly summarize the deficits in network dynamics during sleep in schizophrenia. Then, we discuss today's and tomorrow's non-invasive brain stimulation modalities to engage these network targets.