Neuroimaging in insomnia: Review and reconsiderations

Over the last decades, neuroimaging has become a substantial component of insomnia research. While theoretical underpinnings of different studies vary just like methodological choices and the experimental design, it is suggested that major features of insomnia disorder rely on the impaired function, structure, metabolism and connectivity of brain areas involved in sleep generation, emotion regulation, self-processing/-awareness and attentional orientation. However, neuroimaging research on insomnia often suffers from small sample sizes, heterogeneous methodology and a lack of replicability. With respect to these issues, the field needs to address the questions: (1a) how sufficiently large sample sizes can be accumulated within a reasonable economic framework; (1b) how effect sizes in insomnia-related paradigms can be amplified; (2a) how a higher degree of standardisation and transparency in methodology can be provided; and (2b) how an adequate amount of flexibility/complexity in study design can be maintained. On condition that methodological consistency and a certain degree of adaptability are given, pooled data/large cohort analyses can be considered to be one way to answer these questions. Regarding experimental single-centre trials, it might be helpful to focus on insomnia-related transdiagnostic concepts. In doing so, expectable effect sizes (in between-subjects designs) can be increased by: (a) comparing groups that are truly distinct regarding the variables examined in a concept-specific paradigm; and (b) facilitated, intensified and precise elicitation of a target symptom.

Lack of structural brain alterations associated with insomnia: findings from the ENIGMA-Sleep Working Group

Existing neuroimaging studies have reported divergent structural alterations in insomnia disorder (ID). In the present study, we performed a large-scale coordinated meta-analysis by pooling structural brain measures from 1085 subjects (mean [SD] age 50.5 [13.9] years, 50.2% female, 17.4% with insomnia) across three international Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA)-Sleep cohorts. Two sites recruited patients with ID/controls: Freiburg (University of Freiburg Medical Center, Freiburg, Germany) 42/43 and KUMS (Kermanshah University of Medical Sciences, Kermanshah, Iran) 42/49, while the Study of Health in Pomerania (SHIP-Trend, University Medicine Greifswald, Greifswald, Germany) recruited population-based individuals with/without insomnia symptoms 75/662. The influence of insomnia on magnetic resonance imaging-based brain morphometry using an insomnia brain score was then assessed. Within each cohort, we used an ordinary least-squares linear regression to investigate the link between the individual regional cortical and subcortical volumes and the presence of insomnia symptoms. Then, we performed a fixed-effects meta-analysis across cohorts based on the first-level results. For the insomnia brain score, weighted logistic ridge regression was performed on one sample (Freiburg), which separated patients with ID from controls to train a model based on the segmentation measurements. Afterward, the insomnia brain scores were validated using the other two samples. The model was used to predict the log-odds of the subjects with insomnia given individual insomnia-related brain atrophy. After adjusting for multiple comparisons, we did not detect any significant associations between insomnia symptoms and cortical or subcortical volumes, nor could we identify a global insomnia-related brain atrophy pattern. Thus, we observed inconsistent brain morphology differences between individuals with and without insomnia across three independent cohorts. Further large-scale cross-sectional/longitudinal studies using both structural and functional neuroimaging are warranted to decipher the neurobiology of insomnia.

Associations between sleep health and grey matter volume in the UK Biobank cohort (n = 33 356)

As suggested by previous research, sleep health is assumed to be a key determinant of future morbidity and mortality. In line with this, recent studies have found that poor sleep is associated with impaired cognitive function. However, to date, little is known about brain structural abnormalities underlying this association. Although recent findings link sleep health deficits to specific alterations in grey matter volume, evidence remains inconsistent and reliant on small sample sizes. Addressing this problem, the current preregistered study investigated associations between sleep health and grey matter volume (139 imaging-derived phenotypes) in the UK Biobank cohort (33 356 participants). Drawing on a large sample size and consistent data acquisition, sleep duration, insomnia symptoms, daytime sleepiness, chronotype, sleep medication and sleep apnoea were examined. Our main analyses revealed that long sleep duration was systematically associated with larger grey matter volume of basal ganglia substructures. Insomnia symptoms, sleep medication and sleep apnoea were not associated with any of the 139 imaging-derived phenotypes. Short sleep duration, daytime sleepiness as well as late and early chronotype were associated with solitary imaging-derived phenotypes (no recognizable pattern, small effect sizes). To our knowledge, this is the largest study to test associations between sleep health and grey matter volume. Clinical implications of the association between long sleep duration and larger grey matter volume of basal ganglia are discussed. Insomnia symptoms as operationalized in the UK Biobank do not translate into grey matter volume findings.

Sleep health dimensions and shift work as longitudinal predictors of cognitive performance in the UK Biobank cohort

STUDY OBJECTIVES

The long-term effects of sleep health and shift work on cognitive performance are unclear. In addition, research has been limited by small sample sizes and short follow-up periods. We conducted one of the largest examinations of the longitudinal influence of sleep health dimensions and shift work on cognitive performance in people of middle and old age using data from the UK Biobank. The hypothesis was that poor sleep health and shift work would predict lower cognitive performance.

METHODS

Self-reported sleep duration, daytime sleepiness, insomnia symptoms, chronotype and shift work status were assessed as predictors at baseline. Cognitive performance was operationalised by a touchscreen test battery at follow-up between 7.4 ± 2.2 and 9.0 ± 0.9 years after baseline assessment, depending on the specific task. Models were performed for each cognitive domain including relevant confounders (e.g., depression). The alpha level was set at p<0.01 for all analyses.

RESULTS

The study sample comprised 9,394 participants for the reasoning task, 30,072 for the reaction time task, 30,236 for the visual memory task, 2,019 for the numeric memory task and 9,476 for the prospective memory task. Shift work without night shifts (ß= -2.0x10- 1 ± 6.5x10- 2, p=0.002) and with night shifts (ß= -1.9x10- 1 ± 7.2x10- 2, p=0.010) predicted a significantly reduced performance in the reasoning task. Short sleep duration (ß= -2.4x10- 1 ± 7.9x10- 2, p=0.003) and shift work without night shifts (ß= -3.9x10- 1 ± 1.2x10- 1, p=0.002) predicted a significantly lower performance in the task probing prospective memory.

CONCLUSIONS

Our results suggest that, after controlling for confounding variables, shift work and short sleep duration are important predictors for cognitive performance in people of middle and old age. Further work is required to examine causal mechanisms of the observed associations.

Affect and Arousal in Insomnia: Through a Lens of Neuroimaging Studies

PURPOSE OF REVIEW

Previous research has struggled with identifying clear-cut, objective counterparts to subjective distress in insomnia. Approaching this discrepancy with a focus on hyperarousal and dysfunctional affective processes, studies examining brain structures and neural networks involved in affect and arousal are reviewed and conclusions for an updated understanding of insomnia are drawn.

RECENT FINDINGS

Recent studies found that amygdala reactivity, morphometry and adaptation in insomnia are altered, indicating that processing of negative stimuli is intensified and more lasting. Also, patients with insomnia show aberrant connectivity in the default mode network (DMN) and the salience network (SN), which is associated with subjective sleep disturbances, hyperarousal, maladaptive emotion regulation and disturbed integration of emotional states. The limbic circuit is assumed to play a crucial role in enhanced recall of negative experiences. There is reason to consider insomnia as a disorder of affect and arousal. Dysregulation of the limbic circuit might perpetuate impaired connectivity in the DMN and the SN. However, the interplay between the networks is yet to be researched.

[Interaction of insomnia in old age and associated diseases : Cognitive, behavioral and neurobiological aspects]

The prevalence of insomnia is particularly high in old age. Sleep disturbances and impaired daytime functioning reflected in mood swings and concentration difficulties are often accompanied by other mental disorders such as depression. The objective of this article is to shed light on the role of insomnia in the context of frequent comorbidities in middle and old age. The focus is on the identification of linkage points between insomnia and associated diseases on a neurobiological level; however, possible distinguishing features are also named and deliberations on cognitive behavioral aspects and integrative theories, such as the hyperarousal theory are discussed. In order to provide an outlook for future research opportunities, the UK Biobank is presented as a promising resource of long-term data. Finally, the contents of the preceding deliberations are critically reflected and practical implications for the treatment of older patients with insomnia are derived.