Eus J. W. Van Someren’s research while affiliated with University of Amsterdam and other places

Insomnia disorder, major depressive disorder and anxiety disorders are the most common mental health conditions, with high comorbidity and genetic overlap suggesting shared brain mechanisms. Studies on brain correlates of these disorders have not fully addressed this overlap. Aiming to distinguish shared from specific brain structural and functional properties associated with symptoms of these disorders, this study analyzed multimodal brain imaging data from over 40,000 UK Biobank participants. Functional enrichment analyses were conducted to understand the cognitive-emotional and neurotransmission implications of the identified brain regions and connections. Results showed that smaller cortical surfaces, smaller thalamic volumes, and weaker functional connectivity were linked to more severe symptoms across all symptom types. Several symptom-specific associations were revealed, most commonly in different parts of the amygdala-hippocampal-medial prefrontal circuit. These findings revealed both transdiagnostically shared and unique brain properties that could lead to more directed treatment targets for insomnia, depression, and anxiety.

While standard polysomnography has revealed the importance of the sleeping brain in health and disease, more specific insight into the relevant brain circuits requires high-density electroencephalography (EEG). However, identifying and handling sleep EEG artifacts becomes increasingly challenging with higher channel counts and/or volume of recordings. Whereas manual cleaning is time-consuming, subjective, and often yields data loss (e.g., complete removal of channels or epochs), automated approaches suitable and practical for overnight sleep EEG remain limited, especially when control over detection and repair behavior is desired. Here, we introduce a flexible approach for automated cleaning of multichannel sleep recordings, as part of the free Matlab-based toolbox SleepTrip. Key functionality includes 1) channel-wise detection of various artifact types encountered in sleep EEG, 2) channel- and time-resolved marking of data segments for repair through interpolation, and 3) visualization options to review and monitor performance. Functionality for Independent Component Analysis is also included. Extensive customization options allow tailoring cleaning behavior to data properties and analysis goals. By enabling computationally efficient and flexible automated data cleaning, this tool helps to facilitate fundamental and clinical sleep EEG research.

Disturbed sleep comes in many forms. While the key role of sleep in mental health is undisputed, our understanding of the type of sleeping problems that manifest in the early stages of psychiatric disorders is limited. A sample without psychiatric diagnoses (N = 440, 341 women, 97 men, 2 non-binaries; Mage = 32.1, SD = 9.4, range 18–77) underwent a comprehensive assessment, evaluating eight sleep features and 13 questionnaires on common psychiatric complaints. Results revealed that traits of affect disorders, generalized anxiety, and ADHD had the worst sleep profiles, while autism disorder, eating disorder, and impulsivity traits showed milder sleep issues. Mania was the only trait associated with an overall better sleep profile. Across traits, insomnia and fatigue dominated and sleep variability was least prominent. These findings provide support for both transdiagnostic and disorder-specific targets for prevention and treatment.

Arousal is a central component of many emotional symptoms and can contribute to insomnia. Here we assessed how the timing and fluctuating nature of arousal‐related symptoms over the course of the day relate to insomnia symptom severity. In this study, 361 participants ( M age = 31.9 years, 282 women, 77 men, 2 non‐binary individuals) completed the Insomnia Severity Index to assess severity of insomnia symptoms, followed by repeated ratings of anxiety or nervousness, stress, sleepiness, and feeling down via their mobile phone between ~08:00 hours and 00:00 hours across 1 day. Measures of dynamics included: mean levels across the day; variation (standard deviation); instability (mean squared successive differences); and resistance to change/inertia (first‐order autocorrelation). Time‐of‐day patterns were modelled using generalized additive mixed effects models. Insomnia symptom severity (mean Insomnia Severity Index = 9.1, SD = 5.2, range 0–25) was associated with higher mean levels of all arousal‐related symptoms, and increased instability and variation throughout the day in anxiety or nervousness, stress, and feeling down. Resistance to change (inertia) was not associated with insomnia symptom severity. Generalized additive mixed effects analyses showed that while individuals with more severe insomnia symptoms had elevated symptoms across the entire day, they were especially more anxious or nervous and sleepy in the early morning (~08:00 hours), anxious or nervous, stressed and sleepy in the late afternoon/early evening (~16:00 hours–21:00 hours), and anxious or nervous and stressed in the late evening (~22:00 hours). Remarkably, higher arousal occurred in the presence of high subjective sleepiness. Together these results indicate that insomnia symptom severity is associated with problems with daytime and evening arousal regulation.

Background Insomnia is a highly prevalent disorder associated with numerous adverse health outcomes. Cognitive behavioural therapy for insomnia (CBT-I) is recommended as first-line treatment by clinical guidelines but is accessible to only a minority of patients suffering from insomnia. Internet-delivered CBT-I (iCBT-I) could contribute to the widespread dissemination of this first-line treatment. As there is insufficient evidence regarding non-inferiority, this study directly aims to compare therapist-guided internet-delivered versus face-to-face CBT-I in terms of insomnia severity post-treatment. Furthermore, a health-economic evaluation will be conducted, and potential benefits and disadvantages of therapist-guided iCBT-I will be examined. Methods This study protocol describes a randomised controlled two-arm parallel-group non-inferiority trial comparing therapist-guided iCBT-I with face-to-face CBT-I in routine clinical care. A total of 422 patients with insomnia disorder will be randomised and treated at 16 study centres throughout Germany. Outcomes will be assessed at baseline, 10 weeks after randomisation (post), and 6 months after randomisation (follow-up). The primary outcome is insomnia severity measured using the Insomnia Severity Index. Secondary outcomes include depression-related symptoms, quality of life, fatigue, physical activity, daylight exposure, adverse events related to treatment, and a health-economic evaluation. Finally, potential moderator variables and several descriptive and exploratory outcomes will be assessed (e.g. benefits and disadvantages of internet-delivered treatment). Discussion The widespread implementation of CBT-I is a significant healthcare challenge. The non-inferiority of therapist-guided iCBT-I versus face-to-face CBT-I will be investigated in an adequately powered sample in routine clinical care, with the same therapeutic content and same level of therapist qualifications provided with both interventions. If this trial demonstrates the non-inferiority of therapist-guided iCBT-I, healthcare providers may be more confident recommending this treatment to their patients, contributing to the wider dissemination of CBT-I. Trial registration Trial registration number in the German Clinical Trials Register: DRKS00028153 (https://drks.de/search/de/trial/DRKS00028153). Registered on 16th May 2023.

Background Sleep–wake problems and depressive symptoms are common in people with intellectual disabilities (IDs) and are thought to be related to the unstable sleep–wake rhythm in this population. Previously, we showed that after increasing environmental light exposure, mid‐sleep and sleep onset advanced, and mood improved over a period of 14 weeks after installing environmental dynamic light installations in the living room of people with IDs. We invited participants of that short‐term study to take part in the current study on sleep–wake rhythm, mood and behaviour in older adults with IDs 1 year after installing environmental dynamic light installations in the common living rooms of six group homes. Methods A pre–post study was performed from October 2017 to February 2019. We included 45 participants (63.5 ± 8.5 years, 67% female) from six group home facilities who provided data at baseline (9, 4 and 1 weeks prior to installing light installations), short term (3, 7 and 14 weeks after installing light installations) and 1 year (54 weeks after installing light installations). Wrist activity was measured with actigraphy (GENEActiv) to derive the primary outcome of interdaily stability of sleep–wake rhythms as well as sleep estimates. Mood was measured with the Anxiety, Depression and Mood Scale. Behaviour was measured with the Aberrant Behaviour Checklist. Results One year after installing dynamic lighting, we did not find a change in interdaily stability. Total sleep time decreased ( β = −25.40 min; confidence interval: −10.99, −39.82), and sleep onset time was delayed ( β = 25.63 min; confidence interval: 11.18, 40.08). No effect on mood or behaviour was found. Conclusions We did not find a change in sleep–wake rhythm, mood or behaviour in older persons with IDs living in care facilities 1 year after installing the light. We did find evidence for a long‐term effect on sleep duration and sleep timing. The results have to be interpreted with care as the current study had a limited number of participants. The need for more research on the long‐term effects of enhancing environmental light in ID settings is evident.

Expressions such as 'sleep on it' refer to the resolution of distressing experiences across a night of sound sleep. Sleep is an active state during which the brain reorganizes the synaptic connections that form memories. This Perspective proposes a model of how sleep modifies emotional memory traces. Sleep-dependent reorganization occurs through neurophysiological events in neurochemical contexts that determine the fates of synapses to grow, to survive or to be pruned. We discuss how low levels of acetylcholine during non-rapid eye movement sleep and low levels of noradrenaline during rapid eye movement sleep provide a unique window of opportunity for plasticity in neuronal representations of emotional memories that resolves the associated distress. We integrate sleep-facilitated adaptation over three levels: experience and behaviour, neuronal circuits, and synaptic events. The model generates testable hypotheses for how failed sleep-dependent adaptation to emotional distress is key to mental disorders, notably disorders of anxiety, depression and post-traumatic stress with the common aetiology of insomnia.

Objective While studies suggested that locus coeruleus (LC) neurodegeneration contributes to sleep–wake dysregulation in Alzheimer's disease (AD), the association between LC integrity and circadian rest‐activity patterns remains unknown. Here, we investigated the relationships between 24‐hour rest‐activity rhythms, cognitive trajectories, and autopsy‐derived LC integrity in older adults with and without cortical AD neuropathology. Methods This retrospective study leveraged multi‐modal data from participants of the longitudinal clinical‐pathological Rush Memory and Aging Project. Indices of 24‐hour rest‐activity rhythm fragmentation (intradaily variability) and stability (interdaily stability) were extracted from annual actigraphic recordings, and cognitive trajectories were computed from annual cognitive evaluations. At autopsy, LC neurodegeneration was determined by the presence of hypopigmentation, and cortical AD neuropathology was assessed. Contributions of comorbid pathologies (Lewy bodies, cerebrovascular pathology) were evaluated. Results Among the 388 cases included in the study sample (age at death = 92.1 ± 5.9 years; 273 women), 98 (25.3%) displayed LC hypopigmentation, and 251 (64.7%) exhibited cortical AD neuropathology. Logistic regression models showed that higher rest‐activity rhythm fragmentation, measured up to ~7.1 years before death, was associated with increased risk to display LC neurodegeneration at autopsy (odds ratio [OR] = 1.46, 95% confidence interval [CI 95% ]: 1.16–1.84, p BONF = 0.004), particularly in individuals with cortical AD neuropathology (OR = 1.56, CI 95% : 1.15–2.15, p BONF = 0.03) and independently of comorbid pathologies. In addition, longitudinal increases in rest‐activity rhythm fragmentation partially mediated the association between LC neurodegeneration and cognitive decline (estimate = ‐0.011, CI 95% : ‐0.023–‐0.002, p BONF = 0.03). Interpretation These findings highlight the LC as a neurobiological correlate of sleep–wake dysregulation in AD, and further underscore the clinical relevance of monitoring rest‐activity patterns for improved detection of at‐risk individuals. ANN NEUROL 2024