Insomnia heterogeneity: Characteristics to consider for data-driven multivariate subtyping

Subtypes of Insomnia Disorder Identified by Cortical Morphometric Similarity Network

Insomnia disorder (ID) is a highly heterogeneous psychiatric disease, and the use of neuroanatomical data to objectively define biological subtypes is essential. We aimed to examine the neuroanatomical subtypes of ID by morphometric similarity network (MSN) and the association between MSN changes and specific transcriptional expression patterns. We recruited 144 IDs and 124 healthy controls (HC). We performed heterogeneity through discriminant analysis (HYDRA) and identified subtypes within the MSN strength. Differences in MSN between subtypes and HC were compared, and clinical behavioral differences were compared between subtypes. In addition, we investigated the association between MSN changes and brain gene expression in different ID subtypes using partial least squares regression to assess genetic commonalities in psychiatric disorders and further performed functional enrichment analyses. Two distinct subtypes of ID were identified, each exhibiting different MSN changes compared to HC. Furthermore, subtype 1 is characterized by objective short sleep, impaired cognitive function, and some relationships with major depressive disorder and autism spectrum disorder (ASD). In contrast, subtype 2 has normal objective sleep duration but subjectively reports poor sleep and is only related to ASD. The pathogenesis of subtype 1 may be related to genes that regulate sleep rhythms and sleep-wake cycles. In contrast, subtype 2 is more due to adverse emotion perception and regulation. Overall, these findings provide insights into the neuroanatomical subtypes of ID, elucidating the relationships between structural and molecular aspects of the relevant subtypes.

The benefit of inhibitory control training for insomnia with short sleep duration phenotype: a pilot randomized trial

BACKGROUND

Two phenotypes of insomnia disorder (ID) have been identified based on objective total sleep duration (TST): one with short sleep duration (ISSD) and another with normal sleep duration (INSD). Recent proposals suggested that insomnia with objective short-sleep duration (TST < 7 h) is associated with impaired inhibitory function, leading to a dysregulation of cortical inhibition, which may underlie its prevalence. This study investigated the status of impaired response inhibition in these two phenotypes and examined the potential different effect of response inhibition training on these two phenotypes.

METHODS

Twenty-two healthy controls (HC) and eighty-one patients with ID were recruited, with IDs further categorized into ISSD and INSD (with TST ≥ 7 h). Clinical behavior measures, including the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Pre-sleep Arousal Scale (PSAS), objective sleep characteristics assessed by all-night sleep electroencephalography, and the accuracy of NoGo trials in the Go/NoGo task were compared among the three groups. Subsequently, within each ID phenotype, participants were divided into training and blank control sub-groups. The two training sub-groups completed Adaptive Go/NoGo training task (Through adaptive difficulty adjustment, the task trains participants' inhibitory control) 15 times over 3 weeks, and all IDs were assessed using sleep-related subjective and objective measures and Go/NoGo task before and after the intervention.

RESULTS

ISSD patients exhibited significantly longer sleep latency (p = 0.003) compared to HC, while wakefulness duration (p = 0.004) and light sleep duration (p < 0.001) were shorter than INSD. No significant differences in objective sleep characteristics were observed between INSD and HC. Following adaptive training, the ISSD training sub-group showed decreased scores in PSQI (p = 0.039) and ISI (p = 0.053) compared to their blank control sub-group. In the INSD groups, both training and blank control sub-groups demonstrated reductions in PSQI (p < 0.001), ISI (p < 0.001), and the cognitive arousal sub-dimension of the PSAS scores (p = 0.003) in the post-session test.

CONCLUSIONS

Impaired response inhibition is a characteristic of ISSD, potentially indicating dysfunctional cortical inhibition, whereas INSD pathogenesis may be related to cognitive-emotional arousal. Response inhibition training effectively alleviates sleep problems in ISSD. These findings provide new insights for developing precise intervention strategies in ID.

TRIAL REGISTRATION

The study was prospectively registered on May 30, 2024, in Chinese Clinical Trials registry (ChiCTR2400085063).

Disrupted brain functional asymmetry at rest in patients with major depressive disorder associated with sleep disturbances

Sleep disturbances (SD) are common in major depressive disorder (MDD) patients. Brain functional asymmetry is crucial for understanding MDD pathophysiology. Previous studies using the parameter of asymmetry (PAS) approach have found brain functional asymmetry disruption in MDD. However, this has not been explored in MDD patients with SD. This study examined 26 MDD patients with SD, 34 MDD patients without SD, and 34 healthy controls using resting-state functional magnetic resonance imaging scans. SD symptoms were quantified using the 17-item Hamilton Rating Scale for Depression. PAS approach was used to evaluate functional asymmetry. MDD patients with SD displayed increased PAS in the left middle frontal gyrus (MFG)/inferior frontal gyrus (IFG) and decreased PAS in the left parahippocampal gyrus (PHG) compared to MDD patients without SD. Increased PAS in the left MFG/IFG was positively correlated with SD severity, and a negative correlation was found between decreased PAS in the left PHG and SD scores in all MDD patients. Receiver operating characteristic analysis indicated that increased PAS in the left MFG/IFG and decreased PAS in the left PHG may serve as potential neuroimaging markers to differentiate MDD patients with SD from those without SD with Area Under Curve values of 0.8157 and 0.8068, respectively. These results highlighted that increased PAS in the left MFG/IFG and decreased PAS in the left PHG may be considered a prominent feature associated with SD symptoms of MDD patients, potentially serving as imaging markers to discriminate between MDD patients with and without SD.

Insomnia and stress: the mediating roles of frontoparietal network

Insomnia is a widespread health problem among adults, and it impairs cognitive control and emotional regulation functions. Stress and insomnia are positively correlated, and their vicious cycle has been widely reported. In this study, we explore the neural biomarkers of insomnia from the perspective of whole-brain functional connectivity and investigate the neural mechanisms underlying the association between stress and insomnia. The current study was conducted on a cross-sectional sample (N = 430). First, we investigated the correlation between perceived stress and insomnia. Second, we applied connectome-based predictive modeling (CPM) to determine the neuromarkers of insomnia. Finally, we explored the neural basis underlying the association between perceived stress and insomnia. A significant positive correlation was found between perceived stress and insomnia in the present research. Results of CPM revealed the following as the neural substrates supporting insomnia: the emotion regulation circuit involving repetitive negative thinking and the cognitive control circuit involving attention control. According to further results from mediation analysis, the frontoparietal network supporting cognitive emotion regulation is an important neural mechanism that maintains the correlation between stress and insomnia. The present study offers a profound insight into the alterations of brain activity related to insomnia, and it further investigates the neural underpinnings of the robust association between stress and insomnia. This study also opens new avenues for neural interventions to alleviate stress-related insomnia.

Gene expression is associated with brain function of insomnia disorder, rather than brain structure

Previous research has found brain structural and functional abnormalities in patients with insomnia disorder (ID). However, the relationship between brain abnormalities in ID and brain gene expression is unclear. This study explored the relationship between gene expression and brain structural or functional abnormalities in ID, and we validated the reliability of the results with two independent datasets (discover dataset: healthy control (HC) = 129, ID = 264; validation dataset: HC = 160, ID = 115). Brain imaging results show that ID has abnormal resting-state spontaneous activity, regional homogeneity, and widespread gray matter volume reduction compared to HC. The association analysis results with gene expression further revealed that brain function abnormalities in ID were significantly associated with gene expression, but structural abnormalities were not. This study establishes a link between transcriptional changes and brain functional abnormalities in ID, revealing a genetic basis that may involve several biological pathways. Specifically, these pathways include hormonal regulation of the hypothalamic-pituitary-adrenal (HPA) axis, which plays a crucial role in stress response and sleep regulation; ion transport across membranes, vital for neuronal communication; and inhibitory neuronal regulation, essential for maintaining normal brain function. Furthermore, the ID-related genes are enriched for brain tissue and cortical cells, emphasizing their relevance in understanding the biological underpinnings of ID.

Reduced prefrontal activation during cognitive control under emotional interference in chronic insomnia disorder

This study investigated the altered neural activation underlying cognitive control under emotional and sleep-related interference conditions and its role in subjective sleep disturbance in patients with chronic insomnia disorder. In total, 48 patients with chronic insomnia disorder, and 48 age-, sex- and body mass index-matched controls were included in this study. They completed self-reported questionnaires to assess subjective sleep and emotional distress. A sleep diary was used to evaluate subjective sleep parameters. All participants performed the emotional Stroop task (three blocks each of negative emotional, sleep-related, and neutral words) during functional magnetic resonance imaging assessments. We compared brain activation during the emotional Stroop task between the two groups. We also analysed the correlations between altered neural activation and sleep variables. Less neural activation was detected in the right anterior prefrontal cortex of patients with chronic insomnia disorder than in controls when performing the emotional Stroop task with negative emotional words. The decrease in neural activation was negatively correlated with scores on Pittsburgh Sleep Quality Index, Insomnia Severity Index, and Dysfunctional Beliefs and Attitudes about Sleep Scale. In contrast, they were positively correlated with subjective total sleep time and sleep efficiency as reported in sleep diaries. A decrease in right anterior prefrontal cortex activity under the negative emotional words condition of the emotional Stroop task in patients with chronic insomnia disorder suggests a failure of top-down inhibition of negative emotional stimuli. This failure induces disinhibition of cognitive hyperarousal, manifested as rumination or intrusive worries, and potentially causing subjective sleep disturbances.

The interplay between insomnia symptoms and Alzheimer's disease across three main brain networks

STUDY OBJECTIVES

Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network, and central executive network (CEN).

METHODS

We selected 320 participants from the ADNI database and divided them by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores.

RESULTS

Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterized by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were nonsignificant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD.

CONCLUSIONS

We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.

The heterogeneity of insomnia symptoms for emerging workers in the digital economy: Latent profile and network analysis

Although insomnia symptoms is a common public health issue, few studies pay attention to insomnia symptoms among emerging workers in the digital economy. In this study, a total of 1093 emerging workers were recruited. Latent profile analysis was used to investigate the heterogeneity profiles and the relationship between job characteristics and these profiles. Additionally, core symptoms of insomnia were explored through network analysis. Latent profile analysis identified four insomnia profiles: severe insomnia without daytime dysfunction (8.8%), good sleepers (39.6%), mild insomnia (41.7%), and moderate to severe insomnia (9.9%). Job characteristics (e.g. daily working duration, intensity, and performance measurement system) significantly affected the profiles. Network analysis revealed that four profiles had similar network structures, but the edge and strength were varied. The implication for preventing and intervening insomnia symptoms for emerging workers in the digital economy has been discussed.

Gray matter volume alterations in de novo Parkinson's disease: A mediational role in the interplay between sleep quality and anxiety

OBJECTIVE

Parkinson's disease (PD) is increasingly recognized for its non-motor symptoms, among which emotional disturbances and sleep disorders frequently co-occur. The commonality of neuroanatomical underpinnings for these symptoms is not fully understood. This study is intended to investigate the differences in gray matter volume (GMV) between PD patients with anxiety (A-PD) and those without anxiety (NA-PD). Additionally, it seeks to uncover the interplay between GMV variations and the manifestations of anxiety and sleep quality.

METHODS

A total of 37 A-PD patients, 43 NA-PD patients, and 36 healthy controls (HCs) were recruited, all of whom underwent voxel-based morphometry (VBM) analysis. Group differences in GMV were assessed using analysis of covariance (ANCOVA). Partial correlation between GMV, anxiety symptom, and sleep quality were analyzed. Mediation analysis explored the mediating role of the volume of GMV-distinct brain regions on the relationship between sleep quality and anxiety within the PD patient cohort.

RESULTS

A-PD patients showed significantly lower GMV in the fusiform gyrus (FG) and right inferior temporal gyrus (ITG) compared to HCs and NA-PD patients. GMV in these regions correlated negatively with Hamilton Anxiety Rating Scale (HAMA) scores (right ITG: r = -0.690, p < 0.001; left FG: r = -0.509, p < 0.001; right FG: r = -0.576, p < 0.001) and positively with sleep quality in PD patients (right ITG: r = 0.592, p < 0.001; left FG: r = 0.356, p = 0.001; right FG: r = 0.470, p < 0.001). Mediation analysis revealed that GMV in the FG and right ITG mediated the relationship between sleep quality and anxiety symptoms, with substantial effect sizes accounted for by the right ITG (25.74%) and FG (left: 11.90%, right: 15.59%).

CONCLUSION

This study has shed further light on the relationship between sleep disturbances and anxiety symptoms in PD patients. Given the pivotal roles of the FG and the ITG in facial recognition and the recognition of emotion-related facial expressions, our findings indicate that compromised sleep quality, under the pathological conditions of PD, may exacerbate the reduction in GMV within these regions, impairing the recognition of emotional facial expressions and thereby intensifying anxiety symptoms.

SGLT2 inhibition, circulating proteins, and insomnia: A mendelian randomization study

BACKGROUND

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) initially emerged as oral antidiabetic medication but were subsequently discovered to exhibit pleiotropic actions. Insomnia is a prevalent and debilitating sleep disorder. To date, the causality between SGLT2 inhibitors and insomnia remains unclear. This study aims to evaluate the causality between SGLT2 inhibitors and insomnia and identify potential plasma protein mediators.

METHODS

Using a two-sample Mendelian Randomization (MR) analysis, we estimated the causality of SGLT2 inhibition on insomnia and sleep duration. Additionally, employing a two-step and proteome-wide MR analysis, we evaluated the causal link of SGLT2 inhibition on 4907 circulating proteins and the causality of SGLT2 inhibition-driven plasma proteins on insomnia. We applied a false discovery rate (FDR) correction for multiple comparisons. Furthermore, mediation analyses were used to identify plasma proteins that mediate the effects of SGLT2 inhibition on insomnia.

RESULTS

SGLT2 inhibition was negatively correlated with insomnia (odds ratio [OR] = 0.791, 95 % confidence interval [CI] [0.715, 0.876], P = 5.579*10^-6) and positively correlated with sleep duration (β = 0.186, 95 % CI [0.059, 0.314], P = 0.004). Among the 4907 circulating proteins, diadenosine tetraphosphatase (Ap4A) was identified as being linked to both SGLT2 inhibition and insomnia. Mediation analysis indicated that the effect of SGLT2 inhibition on insomnia partially operates through Ap4A (β = -0.018, 95 % CI [-0.036, -0.005], P = 0.023), with a mediation proportion of 7.7 %.

CONCLUSION

The study indicated a causality between SGLT2 inhibition and insomnia, with plasma Ap4A potentially serving as a mediator.

Daytime sleepiness in insomnia: Are we focusing on what truly matters?

Insomnia, the most prevalent sleep disorder, is commonly associated with other mental and somatic disorders, making it a significant health concern. It is characterized by nighttime symptoms and daytime dysfunction, with sleepiness being a potential criterion for the latter. Sleepiness is a normal physiological state that is typically experienced near usual bedtime, in normal circumstances. In insomnia, it seems somewhat logical the idea that there is significant daytime sleepiness. However, the topic has been the subject of various discussions in sleep medicine, with studies yielding contradictory and inconsistent results. In this article, we aim to critically examine daytime sleepiness in individuals with insomnia disorder and propose an alternative approach to addressing it, both in clinical practice and research settings. It is crucial to further investigate the role of daytime sleepiness in insomnia, particularly by focusing on sleepiness perception as a more relevant dimension to explore in majority of patients. It is plausible that certain insomnia phenotypes are objectively sleepy during the day, but more studies are necessary, particularly with well-defined clinical samples. The implications of assessing sleepiness perception in insomnia for clinical practice are discussed, and new avenues for research are suggested.

Bioactive compounds from Ocimum tenuiflorum and Poria cocos: A novel natural Compound for insomnia treatment based on A computational approach

Insomnia, a widespread public health issue, is associated with substantial distress and daytime functionality impairments and can predispose to depression and cardiovascular disease. Cognitive Behavioral Anti-insomnia therapies including benzodiazepines often face limitations due to patient adherence or potential adverse effects. This study focused on identifying novel bioactive compounds from medicinal plants, aiming to discover and develop new therapeutic agents with low risk-to-benefit ratios using computational drug discovery methods. Through a systematic framework involving compound library preparation, evaluation of drug-likeness and pharmacokinetics, toxicity prediction, molecular docking, and molecular dynamic simulations, two natural compounds such as 2-(4-hydroxy-3-methoxyphenyl)-8-methoxy-6-prop-2-enyl-3,4-dihydro-2H-chromen-3-ol from Ocimum tenuiflorum and 7-(2-hydroxypropan-2-yl)-1,4a-dimethyl-9-oxo-3,4,10,10a-tetrahydro-2H-phenanthrene-1-carboxylic acid from Poria cocos exhibited high binding affinity with orexin receptor type 1 (OX1R) and type 2 (OX2R), surpassing commercial drugs used in insomnia treatment. Additionally, they showed interactions with critical amino acid residues within the receptors that play crucial roles in competitive inhibitor activity, like commercial drugs such as Suvorexant, Lemborexant, and Daridorexant. Further, molecular dynamics simulations of the protein-ligand complexes under conditions that mimic the in vivo environment revealed both compounds' sustained and robust interactions with the OX1R and OX2R, reinforcing their potential as effective therapeutic candidates. Furthermore, upon evaluating both compounds' drug-likeness, pharmacokinetics, and toxicity profiles, it was discerned that they displayed considerable drug-like properties and favorable pharmacokinetics, along with diminished toxicity. The research provides a solid foundation for further exploring and validating these compounds as potential anti-insomnia therapeutics.

Subtyping at-risk adolescents for predicting response toward insomnia prevention program

BACKGROUND

Previous study has shown that a brief cognitive-behavioral prevention insomnia program could reduce 71% risk of developing insomnia among at-risk adolescents. This study aimed to evaluate the differential response to insomnia prevention in subgroups of at-risk adolescents.

METHODS

Adolescents with a family history of insomnia and subthreshold insomnia symptoms were randomly assigned to a 4-week insomnia prevention program or nonactive control group. Assessments were conducted at baseline, 1 week, and 6- and 12-month after the intervention. Baseline sleep, daytime, and mood profiles were used to determine different subgroups by using latent class analysis (LCA). Analyses were conducted based on the intention-to-treat approach.

RESULTS

LCA identified three subgroups: (a) insomnia symptoms only, (b) insomnia symptoms with daytime sleepiness and mild anxiety, and (c) insomnia symptoms with daytime sleepiness, mild anxiety, and depression. The incidence rate of insomnia disorder over the 12-month follow-up was significantly reduced for adolescents receiving intervention in subgroup 3 compared with the controls (hazard ratio [HR] = 0.37; 95% confidence interval [CI]: 0.13-0.99; p = .049) and marginally for subgroup 2 (HR = 0.14; 95% CI: 0.02-1.08; p = .059). In addition, adolescents who received intervention in subgroups 2 and 3 had a reduced risk of excessive daytime sleepiness (subgroup 2: adjusted OR [AdjOR] = 0.45, 95% CI: 0.23-0.87; subgroup 3: AdjOR = 0.32, 95% CI: 0.13-0.76) and possible anxiety (subgroup 2: AdjOR = 0.47, 95% CI: 0.27-0.82; subgroup 3: AdjOR = 0.33, 95% CI: 0.14-0.78) compared with the controls over the 12-month follow-up.

CONCLUSIONS

Adolescents at risk for insomnia can be classified into different subgroups according to their psychological profiles, which were associated with differential responses to the insomnia prevention program. These findings indicate the need for further phenotyping and subgrouping at-risk adolescents to develop personalized insomnia prevention.

Differences in Polysomnographic and Craniofacial Characteristics of Catathrenia Phenotypes: A Cluster Analysis

Purpose

Catathrenia is a rare sleeping disorder characterized by repetitive nocturnal groaning during prolonged expirations. Patients with catathrenia had heterogeneous polysomnographic, comorbidity, craniofacial characteristics, and responses to treatment. Identifying phenotypes of catathrenia might benefit the exploration of etiology and personalized therapy.

Patients and Methods

Sixty-six patients diagnosed with catathrenia by full-night audio/video polysomnography seeking treatment with mandibular advancement devices (MAD) or continuous positive airway pressure (CPAP) were included in the cohort. Polysomnographic characteristics including sleep architecture, respiratory, groaning, and arousal events were analyzed. Three-dimensional (3D) and 2D craniofacial hard tissue and upper airway structures were evaluated with cone-beam computed tomography and lateral cephalometry. Phenotypes of catathrenia were identified by K-mean cluster analysis, and inter-group comparisons were assessed.

Results

Two distinct clusters of catathrenia were identified: cluster 1 (n=17) was characterized to have more males (71%), a longer average duration of groaning events (18.5±4.8 and 12.8±5.7s, p=0.005), and broader upper airway (volume 41,386±10,543 and 26,661±6700 mm3, p<0.001); cluster 2 (n=49) was characterized to have more females (73%), higher respiratory disturbance index (RDI) (median 1.0 [0.3, 2.0] and 5.2 [1.2, 13.3]/h, p=0.009), more respiratory effort-related arousals (RERA)(1 [1, 109] and 32 [13, 57)], p=0.005), smaller upper airway (cross-sectional area of velopharynx 512±87 and 339±84 mm2, p<0.001) and better response to treatment (41.2% and 82.6%, p=0.004).

Conclusion

Two distinct phenotypes were identified in patients with catathrenia, primary catathrenia, and catathrenia associated with upper airway obstruction, suggesting respiratory events and upper airway structures might be related to the etiology of catathrenia, with implications for its treatment.

Deficits in brain default mode network connectivity mediate the relationship between poor sleep quality and anxiety severity

STUDY OBJECTIVES

Chronic insomnia disorder (CID) is a prevalent sleep disorder that frequently cooccurs with anxiety. The association between insomnia and anxiety has been established; however, the neurobiological basis of this relationship remains unclear. This study aimed to investigate the neural markers of CID patients with and without anxiety and to determine whether specific neural connectivity mediates the relationship between insomnia and anxiety.

METHODS

This study included 180 participants, comprising CID patients with anxiety (CID-A), CID patients without anxiety (CID-NA), and good sleep controls. All participants completed self-reported measures of sleep quality and anxiety severity and underwent functional magnetic resonance imaging. Brain functional integration was measured using functional connectivity density (FCD) and resting-state functional connectivity (rsFC). Correlation and mediation analyses were used to examine the relationships among brain connectivity, sleep quality, and anxiety severity.

RESULTS

The CID-NA and CID-A groups showed decreased local FCD in the medial prefrontal cortex (mPFC) and disrupted rsFC between the precuneus and other brain regions. Only the CID-A group exhibited altered long-range FCD in the precuneus and the rsFC between the anterior default mode network (DMN, e.g. mPFC) and posterior DMN (e.g. precuneus). Mediation analysis revealed DMN dysconnectivity underlying the association between poor sleep quality and anxiety symptoms.

CONCLUSIONS

This study identified shared and distinct brain circuit disruptions in the CID-NA and CID-A groups, with deficits in DMN connectivity as a potential neural mechanism through which disrupted sleep augments anxiety. These findings may facilitate the development of personalized therapies for insomnia and associated anxiety problems.

Latent profile of the insomnia severity index: A longitudinal study

STUDY OBJECTIVES

To identify the distinct classification of insomnia symptoms and to explore their association with sleep problems and depression.

METHODS

Latent profile analysis was used to examine patterns of insomnia symptoms in two samples. Discovery and replication samples comprised 1043 (Mean age at baseline = 18.95 ± 0.93 years, 62.2% females) and 729 (Mean age at baseline = 18.71 ± 1.02 years, 66.4% females) college students, respectively. Participants completed measures of sleep problems (insomnia symptoms, sleep quality, susceptibility to insomnia, perceived consequences of insomnia, dream recall frequency, and percentage of recurring nightmares) and other psychological variables (rumination and depression). Binary logistic regression was used to analyze the effects of different types of insomnia symptoms at baseline on sleep problems and depression two years later.

RESULTS

Four classes of insomnia symptoms were identified, and classified as "non-insomnia" (class 1, 45.7%), "mild subjective symptoms but severe subjective feelings" (class 2, 23.9%), "severe subjective symptoms but mild subjective feelings" (class 3, 22.0%), and "high insomnia risk" (class 4, 8.4%), respectively. Compared with the group classified as non-insomnia group, other classifications significantly predicted insomnia two years later, only class 4 significantly predicted depression, and class 3 significantly predicted susceptibility to insomnia, after adjusting gender, insomnia, depression, and susceptibility to insomnia at baseline.

CONCLUSIONS

The findings highlighted the importance of identifying the patterns of insomnia symptoms, and the need for tailored intervention to improve sleep problems. Additionally, when screening for insomnia symptoms, simplified screening using Insomnia Severity Index (ISI) dimensions or items should be considered.

Response inhibition impairment related to altered frontal-striatal functional connectivity in insomnia disorder: A pilot and non-clinical study

BACKGROUND

It is not clear whether and how insomnia disorder (ID) impairs response inhibition ability. Fronto-striatal functional connectivity (FC) plays a critical role in response inhibition and is found be abnormal in patients with ID. In this study, we examined whether insomnia symptoms impair response inhibition in a large non-clinical sample and whether impaired response inhibition is related to abnormal fronto-striatal FC.

METHODS

One hundred and fifteen young ID patients and 160 age and sex-matched healthy controls (HC) underwent resting-state functional magnetic response imaging scans and performed the stop-signal task (SST). Performance of SST, Gray Matter Volumes (GMVs), and connections of brain regions related to fronto-striatal circuits was compared between groups. Further examined the association between response inhibition impairment and fronto-striatal FC.

RESULTS

The behavioral results showed that patients with ID had significantly longer stop-signal reaction time (SSRT) compared with the HC, reflecting the impaired response inhibition among IDs. Brain imaging results showed IDs had decreased GMVs of the Right Superior Frontal (SFG) and left Supplementary Motor area (SMA). Seed-based FC results showed that compared to HC, the ID showed decreased FC between left SMA and left Paracentral lobule, left SMA and right SMA, and right SFG and right Orbital Middle Frontal gyrus, and increased FC between right SFG and right putamen. Meanwhile, the FC between right SFG and putamen was positively correlated with SSRT in IDs.

CONCLUSIONS

The current study found significantly impaired response inhibition among ID and this impairment may be related to abnormal fronto-striatal FC in ID.

Tailoring cognitive behavioural therapy for insomnia across contexts, conditions, and individuals: What do we know, where do we go?

Cognitive behavioural therapy for insomnia (CBT-I) is considered the front-line treatment for insomnia. Despite the demonstrated effectiveness of CBT-I, it is necessary to consider how CBT-I may be tailored to different individuals. The purpose of the present review is to provide a summary of literature on tailoring CBT-I to different individuals and provide directions for future research. This review focused on the following domains of adaptation: (i) tailoring CBT-I components to individuals with comorbid mental or physical health conditions such as comorbid depression and pain; (ii) adapting CBT-I delivery for different contexts in which individuals exist, such as inpatient, educational, and different social/cultural settings, (iii) adapting CBT-I to specific individuals via case-formulation in clinical settings. We highlight current gaps in the exploration of tailored CBT-I, including a lack of research methodology to evaluate tailored interventions, a need for the integration of ongoing individualised assessment to inform treatment, and the necessary involvement of consumers and stakeholders throughout the research and treatment development process. Together, this review showed abundant adaptations in CBT-I already exist in the literature. Future research is needed in understanding when and how to apply adaptations in CBT-I and evaluate the benefits of these adaptations.

Reconsidering sleep perception in insomnia: from misperception to mismeasurement

So-called 'sleep misperception' refers to a phenomenon in which individuals have the impression of sleeping little or not at all despite normal objective measures of sleep. It is unknown whether this subjective-objective mismatch truly reflects an abnormal perception of sleep, or whether it results from the inability of standard sleep recording techniques to capture 'wake-like' brain activity patterns that could account for feeling awake during sleep. Here, we systematically reviewed studies reporting sleep macro- and microstructural, metabolic, and mental correlates of sleep (mis)perception. Our findings suggest that most individuals tend to accurately estimate their sleep duration measured with polysomnography (PSG). In good sleepers, feeling awake during sleep is the rule at sleep onset, remains frequent in the first non-rapid eye movement sleep cycle and almost never occurs in rapid eye movement (REM) sleep. In contrast, there are patients with insomnia who consistently underestimate their sleep duration, regardless of how long they sleep. Unlike good sleepers, they continue to feel awake after the first sleep cycle and importantly, during REM sleep. Their mental activity during sleep is also more thought-like. Initial studies based on standard PSG parameters largely failed to show consistent differences in sleep macrostructure between these patients and controls. However, recent studies assessing sleep with more refined techniques have revealed that these patients show metabolic and microstructural electroencephalography changes that likely reflect a shift towards greater cortical activation during sleep and correlate with feeling awake. We discuss the significance of these correlates and conclude with open questions and possible ways to address them.

The importance and limitations of polysomnography in insomnia disorder-a critical appraisal

The importance polysomnography (PSG) in the diagnosis and treatment process of insomnia disorder (ID) remains highly disputed. This review summarises the state of the science regarding PSG indications and findings in ID, and the indications to conduct PSG in ID as stated by relevant guidelines. It then highlights the most relevant questions regarding the topic, including the relevance of ID subtyping, to allow an individualised pharmacological or psychotherapeutic treatment approach.

Neuroimaging profiles of the negative affective network predict anxiety severity in patients with chronic insomnia disorder: A machine learning study

BACKGROUND

Sleep is instrumental in safeguarding emotional well-being. While the susceptibility to both insomnia and anxiety has been demonstrated to involve intricate brain systems, the neuroimaging profile of chronic insomnia disorder with comorbid anxiety symptoms (CID-A) remains unexplored. Employing machine learning methodologies, this study aims to elucidate the distinct neural substrates underlying CID-A and to investigate whether these cerebral markers can prognosticate anxiety symptoms in patients with insomnia.

METHODS

Functional magnetic resonance imaging (fMRI) data were procured from a relatively large cohort (dataset 1) comprised of 47 CID-A patients, 49 CID patients without anxiety (CID-NA), and 48 good sleeper controls (GSC). Aberrant cerebral functional alterations were assessed through functional connectivity strength (FCS) and resting-state functional connectivity (rsFC). Subsequently, Support Vector Regression (SVR) models were constructed to predict anxiety symptoms in CID patients based on neuroimaging features, which were validated utilizing an external cohort (dataset 2).

RESULTS

In comparison to CID-NA and GSC subjects, CID-A patients exhibited heightened FCS in the right dorsomedial prefrontal cortex (DMPFC), a central hub within the negative affective network. Moreover, the SVR models revealed that DMPFC-related rsFC/FCS features could be employed to predict anxiety symptoms in two independent cohorts of CID patients.

LIMITATION

Modifications in brain functionality might vary across insomnia subtypes.

CONCLUSION

The present findings suggest a potential negative affective network model for the neuropathophysiology of CID accompanied by anxiety. Importantly, the negative affective network pattern may serve as a predictor for anxiety symptoms in CID patients.

Prevalence and associated factors of poor sleep quality among industrial workers in Addis Ababa, Ethiopia: findings from a cross-sectional study

OBJECTIVE

This study aimed to investigate the prevalence and associated factors of poor sleep quality among Bole Lemi Industrial Park workers in Addis Ababa, the capital of Ethiopia.

DESIGN

An institution-based cross-sectional study was conducted from July to August 2022. The data were collected using a validated and standardised Pittsburgh Sleep Quality Index Questionnaire. The collected data were entered into EpiData V.4.6 and analysed using Stata V.14. A multivariable binary logistic regression analysis was conducted to identify factors associated with poor sleep quality. The association was determined using an adjusted OR (AOR) with a 95% CI at a p value of <0.05.

SETTING

The study was conducted in Bole Lemi Industrial Park in Addis Ababa.

PARTICIPANTS

A total of 370 workers participated in this study.

OUTCOME MEASURES

The primary outcome of the study was the prevalence of poor sleep quality.

RESULTS

The total response rate was 87.7%. The majority (260, 70.3%) of the participants were female. The mean (±SD) age of the participants was 30.5 (±10.6) years. The prevalence of poor sleep quality during the last months was found to be 75.4% (n=279) (95% CI: 70.7% to 79.7%). Undiversified dietary intake (AOR: 1.63; 95% CI (1.09 to 2.78)), caffeine consumption more than 250 mg per day (AOR: 2.57; 95% CI (1.12 to 6.05)) and night shift work (AOR: 2.36; 95% CI (1.27 to 4.41)) were risk factors for poor sleep quality among sampled workers.

CONCLUSION

This study detected that poor sleep quality is highly prevalent among garment and textile industry workers, indicating that it is a significant public health issue that requires immediate attention. Therefore, modifications of the work environment involving night shift work and the improvement of workers' personal lifestyles involving dietary diversification and caffeine consumption are needed to minimise the burden of poor sleep quality among workers.

Convergent abnormality in the subgenual anterior cingulate cortex in insomnia disorder: A revisited neuroimaging meta-analysis of 39 studies

The neurobiological underpinnings of insomnia disorder (ID) are still poorly understood. A previous meta-analysis conducted by our research group in 2018 revealed no consistent regional alterations based on the limited number of eligible studies. Given the number of studies published during the last few years, we revisited the meta-analysis to provide an update to the field. Following the best-practice guidelines for conducting neuroimaging meta-analyses, we searched several databases (PubMed, Web of Science, and BrainMap) and identified 39 eligible structural and functional studies, reporting coordinates reflecting significant group differences between ID patients and healthy controls. A significant convergent regional alteration in the subgenual anterior cingulate cortex (sgACC) was observed using the activation likelihood estimation algorithm. Behavioural decoding using the BrainMap database indicated that this region is involved in fear-related emotional and cognitive processing. The sgACC showed robust task-based co-activation in meta-analytic connectivity modelling and task-free functional connectivity in a resting-state functional connectivity analysis with the main hubs of the salience and default mode networks, including the posterior cingulate cortex and dorsal ACC, amygdala, hippocampus, and medial prefrontal cortex. Collectively, the findings from this large-scale meta-analysis suggest a critical role of the sgACC in the pathophysiology of ID.

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 signs of sleep bruxism and insomnia: A polysomnographic study

Sleep bruxism (SB) is a repetitive jaw-muscle activity characterised by clenching or grinding of the teeth and/or by bracing or thrusting of the mandible. Sleep bruxism has been linked with insomnia symptoms. Moreover, it has been suggested that there is a positive association between distress and the occurrence of sleep bruxism. However, the occurrence of sleep bruxism and its association with distress have not been studied in patients with insomnia. Therefore, we hypothesised that: (1) the occurrence of sleep bruxism is higher in patients with insomnia than in healthy controls; and (2) the occurrence of sleep bruxism in insomnia patients with moderate to high distress (IMHD) is higher than that in insomnia patients with slight distress (ISD). A total of 44 controls (34 females, 10 males, mean ± SD age = 46.8 ± 14.4 years) and 42 participants with insomnia (35 females, 7 males, mean ± SD age = 51.3 ± 12.1 years) were enrolled in this study. Among 42 participants with insomnia, 20 participants were subtyped as IMHD, 17 participants as ISD. Another five participants were not subtyped due to insufficient information. Group differences in rhythmic masticatory muscle activity (RMMA), a biomarker of sleep bruxism, were evaluated with Mann-Whitney U tests. The medians and interquartile ranges of the RMMA indices were 0.8|1.8|3.3 in controls, 1.1|1.6|2.3 in IMHD and 1.2|1.9|2.9 in ISD. There was no significant difference in the RMMA index, neither between participants with insomnia and controls (P = 0.514) nor between IMHD versus ISD (P = 0.270). The occurrence of RMMA indicators of possible sleep bruxism is not significantly different between individuals with insomnia and controls, nor between IMHD versus ISD.

Mind, Body and Machine: Preliminary Study to Explore Predictors of Treatment Response After a Sleep Robot Intervention for Adults with Insomnia

Introduction

The study aimed to explore characteristics of responders to a sleep robot intervention for adults with insomnia, and the likelihood that participants responded to the intervention.

Methods

Data from the intervention and the control group in a randomized waitlist-controlled trial (n = 44) were pooled together after both had undergone the intervention. A repeated measures ANOVA and Friedman tests were used to explore changes over time. Differences in baseline characteristics between responders (n = 13), defined as a reduction of -5 on the Insomnia Severity Index from pre- to post-intervention, and non-responders (n = 31) were analyzed with t-tests and chi-square tests. Finally, logistic regression models were estimated.

Results

Baseline anxiety was the only statistically significant difference between responders and non-responders (p = 0.03). A logistic regression model with anxiety and sleep quality as predictors was statistically significant, correctly classifying 83.3% of cases.

Discussion

The results imply that people with lower anxiety and higher sleep quality at baseline are more likely to report clinically significant improvements in insomnia from the sleep robot intervention.

Subtypes of insomnia revealed by the heterogeneity of neuroanatomical patterns: a structural MRI study

The current conflicting neuroimaging findings of insomnia disorder (ID) may be attributed to heterogeneity in ID. The present study aims to clarify the high heterogeneity in ID and examine the objective neurobiological subtypes of ID by using a novel machine learning method based on gray matter volumes (GMVs). We recruited 56 patients with ID and 73 healthy controls (HCs). The T1-weighted anatomical images were obtained for each participant. We investigated whether the ID has higher interindividual heterogeneity in GMVs. Then, we used a heterogeneous machine learning algorithm by discriminative analysis (HYDRA) to identify subtypes of ID with features of brain regional GMVs. We found that patients with ID have higher interindividual variability than HCs. HYDRA identified two distinct and reliable neuroanatomical subtypes of ID. Two subtypes showed significantly different aberrance in GMVs compared with HCs. Specifically, subtype 1 exhibited widespread decreased GMVs in some brain regions, including the right inferior temporal gyrus, left superior temporal gyrus, left precuneus, right middle cingulate, and right supplementary motor area. Subtype 2 only demonstrated increased GMVs in the right superior temporal gyrus. Additionally, the GMVs of altered brain regions in subtype 1 were significantly correlated with daytime functioning, but in subtype 2, they were significantly correlated with sleep disturbance. These results explain conflicting neuroimaging findings and propose a potential objective neurobiological classification contributing to ID's precise clinical diagnosis and treatment. DATA AND CODE AVAILABILITY: The source and means of obtaining the data used in the study have been described fully in the Methods and Materials section. The codes and data in this study are available upon a reasonable request to the corresponding author.

Discriminating Paradoxical and Psychophysiological Insomnia Based on Structural and Functional Brain Images: A Preliminary Machine Learning Study

Insomnia disorder (ID) is a prevalent mental illness. Several behavioral and neuroimaging studies suggested that ID is a heterogenous condition with various subtypes. However, neurobiological alterations in different subtypes of ID are poorly understood. We aimed to assess whether unimodal and multimodal whole-brain neuroimaging measurements can discriminate two commonly described ID subtypes (i.e., paradoxical and psychophysiological insomnia) from each other and healthy subjects. We obtained T1-weighted images and resting-state fMRI from 34 patients with ID and 48 healthy controls. The outcome measures were grey matter volume, cortical thickness, amplitude of low-frequency fluctuation, degree centrality, and regional homogeneity. Subsequently, we applied support vector machines to classify subjects via unimodal and multimodal measures. The results of the multimodal classification were superior to those of unimodal approaches, i.e., we achieved 81% accuracy in separating psychophysiological vs. control, 87% for paradoxical vs. control, and 89% for paradoxical vs. psychophysiological insomnia. This preliminary study provides evidence that structural and functional brain data can help to distinguish two common subtypes of ID from each other and healthy subjects. These initial findings may stimulate further research to identify the underlying mechanism of each subtype and develop personalized treatments for ID in the future.

Group-delivered cognitive behavioural therapy versus waiting list in the treatment of insomnia in primary care: study protocol for a pragmatic, multicentre randomized controlled trial

BACKGROUND

Insomnia is common in the general population and is a risk factor for ill-health, which highlights the importance of treating insomnia effectively and cost-efficiently. Cognitive-behavioural therapy for insomnia (CBT-I) is recommended as first-line treatment due to its long-term effectiveness and few side-effects, but its availability is limited. The aim of this pragmatic, multicentre randomized controlled trial is to investigate the effectiveness of group-delivered CBT-I in primary care compared to a waiting-list control group.

METHODS

A pragmatic multicentre randomized controlled trial will be conducted with about 300 participants recruited across 26 Healthy Life Centres in Norway. Participants will complete online screening and provide consent before enrolment. Those who meet the eligibility criteria will be randomized to a group-delivered CBT-I or to a waiting list according to a 2:1 ratio. The intervention consists of four two-hour sessions. Assessments will be performed at baseline, 4 weeks, 3- and 6 months post-intervention, respectively. The primary outcome is self-reported insomnia severity at 3 months post-intervention. Secondary outcomes include health-related quality of life, fatigue, mental distress, dysfunctional beliefs and attitudes about sleep, sleep reactivity, 7-day sleep diaries, and data obtained from national health registries (sick leave, use of relevant prescribed medications, healthcare utilization). Exploratory analyses will identify factors influencing treatment effectiveness, and we will conduct a mixed-method process evaluation to identify facilitators and barriers of participants' treatment adherence. The study protocol was approved by the Regional Committee for Medical and Health Research ethics in Mid-Norway (ID 465241).

DISCUSSION

This large-scale pragmatic trial will investigate the effectiveness of group-delivered cognitive behavioural therapy versus waiting list in the treatment of insomnia, generating findings that are generalizable to day-to-day treatment of insomnia in interdisciplinary primary care services. The trial will identify those who would benefit from the group-delivered therapy, and will investigate the rates of sick leave, medication use, and healthcare utilization among adults who undergo the group-delivered therapy.

TRIAL REGISTRATION

The trial was retrospectively registered in the ISRCTN registry (ISRCTN16185698).

Do better nights lead to better days? Guided internet-based cognitive behavioral therapy for insomnia in people suffering from a range of mental health problems: Protocol of a pragmatic randomized clinical trial

BACKGROUND

Insomnia is the transdiagnostically shared most common complaint in disorders of anxiety, stress and emotion regulation. Current cognitive behavioral therapies (CBT) for these disorders do not address sleep, while good sleep is essential for regulating emotions and learning new cognitions and behaviours: the core fundaments of CBT. This transdiagnostic randomized control trial (RCT) evaluates whether guided internet-delivered cognitive behavioral therapy for insomnia (iCBT-I) (1) improves sleep, (2) affects the progression of emotional distress and (3) enhances the effectiveness of regular treatment of people with clinically relevant symptoms of emotional disorders across all mental health care (MHC) echelons.

METHODS

We aim for 576 completers with clinically relevant symptoms of insomnia as well as at least one of the dimensions of generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder (PD), posttraumatic stress disorder (PTSD) or borderline personality disorder (BPD). Participants are either pre-clinical, unattended, or referred to general- or specialized MHC. Using covariate-adaptive randomization, participants will be assigned to a 5 to 8-week iCBT-I (i-Sleep) or a control condition (sleep diary only) and assessed at baseline, and after two and eight months. The primary outcome is insomnia severity. Secondary outcomes address sleep, severity of mental health symptoms, daytime functioning, mental health protective lifestyles, well-being, and process evaluation measures. Analyses use linear mixed-effect regression models.

DISCUSSION

This study can reveal for whom, and at which stage of disease progression, better nights could mean substantially better days.

TRIAL REGISTRATION

International Clinical Trial Registry Platform (NL9776). Registered on 2021-10-07.

Actigraphy in studies on insomnia: Worth the effort?

In the past decades, actigraphy has emerged as a promising, cost-effective, and easy-to-use tool for ambulatory sleep recording. Polysomnography (PSG) validation studies showed that actigraphic sleep estimates fare relatively well in healthy sleepers. Additionally, round-the-clock actigraphy recording has been used to study circadian rhythms in various populations. To this date, however, there is little evidence that the diagnosis, monitoring, or treatment of insomnia can significantly benefit from actigraphy recordings. Using a case-control design, we therefore critically examined whether mean or within-subject variability of actigraphy sleep estimates or circadian patterns add to the understanding of sleep complaints in insomnia. We acquired actigraphy recordings and sleep diaries of 37 controls and 167 patients with varying degrees of insomnia severity for up to 9 consecutive days in their home environment. Additionally, the participants spent one night in the laboratory, where actigraphy was recorded alongside PSG to check whether sleep, in principle, is well estimated. Despite moderate to strong agreement between actigraphy and PSG sleep scoring in the laboratory, ambulatory actigraphic estimates of average sleep and circadian rhythm variables failed to successfully differentiate patients with insomnia from controls in the home environment. Only total sleep time differed between the groups. Additionally, within-subject variability of sleep efficiency and wake after sleep onset was higher in patients. Insomnia research may therefore benefit from shifting attention from average sleep variables to day-to-day variability or from the development of non-motor home-assessed indicators of sleep quality.

Targeting Orexin Receptors for the Treatment of Insomnia: From Physiological Mechanisms to Current Clinical Evidence and Recommendations

After a detailed description of orexins and their roles in sleep and other medical disorders, we discuss here the current clinical evidence on the effects of dual (DORAs) or selective (SORAs) orexin receptor antagonists on insomnia with the aim to provide recommendations for their further assessment in a context of personalized and precision medicine. In the last decade, many trials have been conducted with orexin receptor antagonists, which represent an innovative and valid therapeutic option based on the multiple mechanisms of action of orexins on different biological circuits, both centrally and peripherally, and their role in a wide range of medical conditions which are often associated with insomnia. A very interesting aspect of this new category of drugs is that they have limited abuse liability and their discontinuation does not seem associated with significant rebound effects. Further studies on the efficacy of DORAs are required, especially on children and adolescents and in particular conditions, such as menopause. Which DORA is most suitable for each patient, based on comorbidities and/or concomitant treatments, should be the focus of further careful research. On the contrary, studies on SORAs, some of which seem to be appropriate also in insomnia in patients with psychiatric diseases, are still at an early stage and, therefore, do not allow to draw definite conclusions.

Diagnostic identification of chronic insomnia using ALFF and FC features of resting-state functional MRI and logistic regression approach

This study investigated whether the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) features could be used as potentially neurological markers to identify chronic insomnia (CI) using resting-state functional MRI and machine learning method logistic regression (LR). This study included 49 CI patients and 47 healthy controls (HC). Voxel-wise features, including the amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC), were extracted from resting-state functional magnetic resonance brain images. Then, we divided the data into two independent cohorts for training (44 CI patients and 42 HC patients), and independent validation (5 CI patients and 5 HC patients) by using logistic regression. The model was evaluated using 20 rounds of fivefold cross‑validation for training. In particular, a two-sample t-test (GRF corrected, p-voxel < 0.001, p-cluster < 0.05) was used for feature selection during the model training. Finally, single‑shot testing of the final model was performed on the independent validation cohort. A correlation analysis (Bonferroni correction, p < 0.05/4) was also conducted to determine whether the features contributing to the prediction were correlated with clinical characteristics, including the Insomnia Severity Index (ISI), Pittsburgh sleep quality index (PSQI), self-rating anxiety scale (SAS), and self-rating depression scale (SDS). Results showed that resting-state features had a discrimination accuracy of 86.40%, with a sensitivity of 93.00% and specificity of 79.80%. The area under the curve (AUC) was 0.89 (all [Formula: see text]< 0.001). The ALFF and FC features showed significant differences between the CI patients and HC. The regions contributing to the prediction mainly included the anterior cingulate, prefrontal cortex, orbital part of the frontal lobe, angular gyrus, cingulate gyrus, praecuneus, parietal lobe, temporal gyrus, superior temporal gyrus, and middle temporal gyrus. Furthermore, some specific functional connectivity among related regions was positively correlated with the ISI, and also negatively related to the SDS in correlation analysis. Our current study suggested that ALFF and FC in the regions contributing to diagnostic identification might serve as potential neuromarkers for CI.

The top 100 most cited papers in insomnia: A bibliometric analysis

Objective

The number of citations to a paper represents the weight of that work in a particular area of interest. Several highly cited papers are listed in the bibliometric analysis. This study aimed to identify and analyze the 100 most cited papers in insomnia research that might appeal to researchers and clinicians.

Methods

We reviewed the Web of Science (WOS) Core Collection database to identify articles from 1985 to 24 March 2022. The R bibliometric package was used to further analyze citation counts, authors, year of publication, source journal, geographical origin, subject, article type, and level of evidence. Word co-occurrence in 100 articles was visualized using VOS viewer software.

Results

A total of 44,654 manuscripts were searched on the Web of Science. Between 2001 and 2021, the top 100 influential manuscripts were published, with a total citation frequency of 38,463. The top countries and institutions contributing to the field were the U.S. and Duke University. Morin C.M. was the most productive author, ranking first in citations. Sleep had the highest number of manuscripts published in the top 100 (n = 31), followed by Sleep Medicine Reviews (n = 9). The most cited manuscript (Bastien et al., Sleep Medicine, 2001; 3,384 citations) reported clinical validation of the Insomnia Severity Index (ISI) as a brief screening indicator for insomnia and as an outcome indicator for treatment studies. Co-occurrence analyses suggest that psychiatric disorders combined with insomnia and cognitive behavioral therapy remain future research trends.

Conclusion

This study provides a detailed list of the most cited articles on insomnia. The analysis provides researchers and clinicians with a detailed overview of the most cited papers on insomnia over the past two decades. Notably, COVID-19, anxiety, depression, CBT, and sleep microstructure are potential areas of focus for future research.

Dynamic changes in fractional amplitude of low-frequency fluctuations in patients with chronic insomnia

BACKGROUND

Previous neuroimaging studies have mostly focused on changes in static functional connectivity in patients with chronic insomnia (CI) . Features of dynamic brain activity in patients with CI have rarely been described in detail. The present study investigated changes in dynamic intrinsic brain activity in patients with CI by dynamic fractional amplitude of low-frequency fluctuation (dfALFF) analysis.

MATERIALS AND METHODS

A total of 30 patients with CI and 27 healthy controls (HCs) were enrolled. We compared dfALFF between these two groups, and examined the correlation between changes in dfALFF and clinical symptoms of CI. Multivariate pattern analysis was performed to differentiate patients with CI from HCs.

RESULTS

Compared with HC subjects, patients with CI showed significantly increased dfALFF in the left insula, right superior temporal gyrus, left parahippocampal gyrus, right amygdala, and bilateral posterior lobes of the cerebellum. Moreover, dfALFF values in the left insula and left parahippocampal gyrus showed a positive correlation with Pittsburgh Sleep Quality Index scores. A logistic regression model was constructed that had 96.7% sensitivity, 80.0% specificity, and 83.0% overall accuracy for distinguishing patients with CI from HCs.

CONCLUSION

Dynamic local brain activity showed increased instability in patients with CI. The variability in dfALFF in the limbic system and brain areas related to sleep/wakefulness was associated with insomnia symptoms. These findings may provide insight into the neuropathologic basis of CI.

The role of ascending arousal network in patients with chronic insomnia disorder

The ascending arousal system plays a crucial role in individuals' consciousness. Recently, advanced functional magnetic resonance imaging (fMRI) has made it possible to investigate the ascending arousal network (AAN) in vivo. However, the role of AAN in the neuropathology of human insomnia remains unclear. Our study aimed to explore alterations in AAN and its connections with cortical networks in chronic insomnia disorder (CID). Resting-state fMRI data were acquired from 60 patients with CID and 60 good sleeper controls (GSCs). Changes in the brain's functional connectivity (FC) between the AAN and eight cortical networks were detected in patients with CID and GSCs. Multivariate pattern analysis (MVPA) was employed to differentiate CID patients from GSCs and predict clinical symptoms in patients with CID. Finally, these MVPA findings were further verified using an external data set (32 patients with CID and 33 GSCs). Compared to GSCs, patients with CID exhibited increased FC within the AAN, as well as increased FC between the AAN and default mode, cerebellar, sensorimotor, and dorsal attention networks. These AAN-related FC patterns and the MVPA classification model could be used to differentiate CID patients from GSCs with 88% accuracy in the first cohort and 77% accuracy in the validation cohort. Moreover, the MVPA prediction models could separately predict insomnia (data set 1, R²  = .34; data set 2, R²  = .15) and anxiety symptoms (data set 1, R²  = .35; data set 2, R²  = .34) in the two independent cohorts of patients. Our findings indicated that AAN contributed to the neurobiological mechanism of insomnia and highlighted that fMRI-based markers and machine learning techniques might facilitate the evaluation of insomnia and its comorbid mental symptoms.

A large collection of real-world pediatric sleep studies

Despite being crucial to health and quality of life, sleep-especially pediatric sleep-is not yet well understood. This is exacerbated by lack of access to sufficient pediatric sleep data with clinical annotation. In order to accelerate research on pediatric sleep and its connection to health, we create the Nationwide Children's Hospital (NCH) Sleep DataBank and publish it at Physionet and the National Sleep Research Resource (NSRR), which is a large sleep data common with physiological data, clinical data, and tools for analyses. The NCH Sleep DataBank consists of 3,984 polysomnography studies and over 5.6 million clinical observations on 3,673 unique patients between 2017 and 2019 at NCH. The novelties of this dataset include: (1) large-scale sleep dataset suitable for discovering new insights via data mining, (2) explicit focus on pediatric patients, (3) gathered in a real-world clinical setting, and (4) the accompanying rich set of clinical data. The NCH Sleep DataBank is a valuable resource for advancing automatic sleep scoring and real-time sleep disorder prediction, among many other potential scientific discoveries.

Sleep Quality and Insomnia Severity among Italian University Students: A Latent Profile Analysis

Insomnia is a widespread sleep disorder associated with physical and mental health conditions. Although the heterogeneity of insomnia presentations has been acknowledged, research investigating clinically meaningful insomnia subtypes is still ongoing. This study aimed at exploring insomnia subtypes according to widely-used measures of symptoms severity and sleep quality among Italian university students using a latent profile analysis. Data were collected from 490 students reporting relevant insomnia symptoms through an online cross-sectional survey comprising the Insomnia Severity Index, the Pittsburgh Sleep Quality Index, the 21-item Depression Anxiety Stress Scale, and the Short Form-12. Latent profile analysis identified five insomnia subtypes. The severe insomnia (8.8%) group showed the highest insomnia severity, with diverse complaints concerning sleep quality and daytime functioning. Moderate insomnia with sleep duration complaints (8.4%) and moderate insomnia with medication use (15.9%) subgroups were characterized by middle range insomnia severity, with problems of sleep continuity and sleep medication use, respectively. Subthreshold insomnia with sleep latency complaints (20.4%) and subthreshold insomnia (46.5%) groups showed attenuated insomnia symptoms. Higher psychological complaints and worse quality of life were associated with greater sleep complaints. Overall, these findings highlight the relevance of sleep quality domains in identifying insomnia subtypes and might help optimize insomnia treatments.

Insomnia Symptoms and Daytime Fatigue Co-Occurrence in Adolescent and Young Adult Childhood Cancer Patients in Follow-Up after Treatment: Prevalence and Associated Risk Factors

Insomnia symptoms and daytime fatigue commonly occur in pediatric oncology, which significantly impact physical and psychosocial health. This study evaluated the prevalence of insomnia only, daytime fatigue only, the co-occurrence of insomnia−daytime fatigue symptoms, and associated risk factors. Childhood cancer patients (n = 565, 12−26 years old, ≥6 months after treatment) participated in a national, cross-sectional questionnaire study, measuring insomnia symptoms (ISI; Insomnia Severity Index) and daytime fatigue (single item). Prevalence rates of insomnia and/or daytime fatigue subgroups and ISI severity ranges were calculated. Multinomial regression models were applied to assess risk factors. Most patients reported no insomnia symptoms or daytime fatigue (61.8%). In the 38.2% of patients who had symptoms, 48.1% reported insomnia and daytime fatigue, 34.7% insomnia only, and 17.1% daytime fatigue only. Insomnia scores were higher in patients with insomnia−daytime fatigue compared to insomnia only (p < 0.001). Risk factors that emerged were: female sex and co-morbidities (all), shorter time after treatment and bedtime gaming (insomnia only), young adulthood (insomnia−fatigue/fatigue only), needing someone else to fall asleep and inconsistent wake times (both insomnia groups), lower educational level and consistent bedtimes (insomnia−fatigue). Insomnia symptoms and daytime fatigue are common and often co-occur. While current fatigue guidelines do not include insomnia symptoms, healthcare providers should inquire about insomnia as this potentially provides additional options for treatment and prevention.

Chronic insomnia of early childhood: Phenotypes and pathophysiology

This paper aims to review the limitations of the current classification of insomnia of early childhood and propose a new conceptual model allowing a better understanding of its pathophysiology. Our hypothesis is that chronic insomnia of childhood has different phenotypical expressions, associated to different pathophysiological mechanisms. Based on a long-lasting experience in evaluating a very large number of children with specific insomnia symptoms (nocturnal awakenings, difficulty in falling asleep, nocturnal restlessness, early morning awakenings) and on published data, we hypothesize that different phenotypes of insomnia might exist with different therapeutic implications. We describe three phenotypes of insomnia in early childhood: a) insomnia with motor restlessness; b) insomnia characterized without difficulties in falling asleep but with long-lasting early morning awakenings; c) insomnia with multiple night awakenings and falling asleep difficulty. This type of categorization might have important implications for treatment, based on the different hypothetical neurotransmitter dysfunctions. The early identification of a phenotype of insomnia might guide to specific behavioral and/or pharmacological interventions with the aim to prevent chronic insomnia.

Clinical characterization of insomnia in adolescents - an integrated approach to psychopathology

OBJECTIVES/BACKGROUND

Insomnia in adolescence is common and debilitating yet it remains poorly understood. Here, we examine the complexity of clinical, behavioral, and psychosocial factors characterizing insomnia in adolescents.

METHODS

Ninety-five adolescents (16-19 years) with (N = 47, 31 female) and without (N = 48, 28 female) insomnia symptoms participated. In the insomnia group, 26 (20 female) met full DSM-5 criteria for insomnia disorder, while 21 (11 female) met partial criteria. Participants completed a clinical interview and assessments of clinical, behavioral, and psychosocial dimensions associated with insomnia. GLMs and network analyses were used to evaluate group and sex differences in severity and inter-relationships between symptoms.

RESULTS

Adolescents with insomnia symptomatology had lower sleep hygiene and thought control, more depressive symptoms and dysfunctional sleep-related cognitions, and more substance use as a coping behavior than healthy controls. They also indicated higher neuroticism, stress levels, and sleep stress reactivity (p < 0.05), but no difference in adverse childhood experiences, than controls. Girls compared to boys with insomnia reported lower sleep quality, and more pre-sleep cognitive activity and sleep stress reactivity (p < 0.05). Compared to healthy girls, girls in the insomnia group reported lower sleep hygiene and higher agreeableness. Network analyses confirmed profound group differences in network topology, with the insomnia group having different levels of centrality and relationships between clinical characteristics compared with controls.

CONCLUSIONS

Findings highlight clinical and sex-specific characteristics of adolescent insomnia, with network analyses revealing a complex interplay between clinical, behavioral, and psychosocial domains. Adolescents with insomnia symptoms, particularly girls, may benefit from interventions to improve negative cognition, mood, and stress, and behavioral strategies to counteract sleep-related maladaptive behaviors.

Poor Sleep Quality and Factors Among Reproductive-Age Women in Southwest Ethiopia

BACKGROUND

Adequate sleep is vital for physical and mental wellbeing. Sleep-related problems including poor quality of sleep have been increasing throughout the world among reproductive-aged women. Poor sleep quality has been related with number of diseases and health problems However, evidences are scarce regarding poor sleep quality and its associated factors among women of the reproductive age group in Ethiopia.

OBJECTIVE

To assess sleep quality and associated factors among women of reproductive age group in Mizan Aman town, Southwest Ethiopia.

METHOD

Community-based cross-sectional study was conducted among 606 reproductive-aged women from 06 November to 20 December 2020, in Mizan Aman town. Data were collected using structured interview administered questionnaires. Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. Multivariable logistic regression was applied using an adjusted odds ratio with a corresponding 95% confidence interval to evaluate the statistical significance of associated factors.

RESULT

The overall prevalence of poor sleep quality was 71.3%. The late age group of 42-49 (AOR, 95% CI; 1.21 (1.08-5.76), palpable/visible thyroid gland (AOR, 95% CI; 2. 12 (1.08-3.82), current substance use (AOR, 95% CI; 1.76 (1.11-6.10) and having premenstrual syndrome (AOR, 95% CI; 1.86 (1.38-3.12) were significantly associated with poor sleep quality among reproductive age group women.

CONCLUSION

Significant majority of reproductive age group women faced poor sleep quality. Therefore, screening of sleep patterns among this particular age group is warranted. Moreover, education about sleep hygiene needs to be given considering the identified factors to improve sleep quality.

Sleep difficulties, incident dementia and all-cause mortality among older adults across 8 years: Findings from the National Health and Aging Trends Study

Sleep difficulties have been implicated in the development and progression of dementia and in all-cause mortality. This study examines the relationship between sleep difficulties, incident dementia and all-cause mortality over 8 years of follow-up among a nationally representative sample of older (≥65 years) adults in the United States. We used data collected from the National Health and Aging Trends Study (NHATS) from 2011 to 2018, a prospective cohort study of Medicare beneficiaries. At baseline, the NHATS sample comprised 6,376 older adults who were representative of 32 million older adults. Respondents reported routine difficulty initiating sleep or difficulty falling back asleep "most nights" or "every night" in each study year. In each year, dementia was determined by either self-reported diagnosis or performance on immediate and delayed recall word and clock drawing tests, whereas all-cause mortality was determined by proxy. We conducted Cox proportional hazards modelling, adjusting for age, sex, marital status and chronic conditions. In models predicting all-cause mortality, we also controlled for dementia. Among respondents at baseline, 19% were 65-75 years of age, 71% identified as non-Hispanic white and 59% were female. Difficulty initiating sleep (hazard ratio [HR], 1.49; 95% confidence interval [CI],1.25-1.77), difficulty falling back asleep (HR, = 1.39; 95% CI,1.14-1.70) and concurrent sleep difficulties (HR, 1.58; 95% CI, 1.25-1.99) were associated with greater risk of dementia. Difficulty initiating sleep (HR, 1.44; 95% CI,1.20-1.72), difficulty falling back asleep (HR, 1.56; 95% CI,1.29-1.89), and concurrent sleep difficulties (HR, 1.80; 95% CI, 1.44-2.24) were associated with greater risk of all-cause mortality. Our findings demonstrate that reported difficulties are prospectively associated with an increased risk of dementia and all-cause mortality among older people.

Subtypen der Insomnie – exemplarische Ansätze und offene Fragen

Verschiedene Autorinnen und Autoren nehmen an, dass es klinisch nützlich und wissenschaftlich erkenntnisbringend sein könnte, Subtypen der Insomnie zu identifizieren, um diese spezifisch und damit möglicherweise effektiver zu behandeln, als dies derzeit geschieht. Im vorliegenden Beitrag werden folgende exemplarisch ausgewählte Ansätze zur Einteilung der Insomnie in Subtypen vorgestellt: 1) Einteilungen nach klinischen Symptomen; 2) Primäre vs. sekundäre Insomnie; 3) Subtypen nach ICSD‑2; 4) Insomnie mit und ohne objektiv messbare kurze Schlafdauer; 5) Subtypen aus der Netherlands Sleep Registry. Anschließend werden die Stabilität der Zuordnung von einzelnen Patienten zu den verschiedenen Subtypen sowie die klinische Relevanz der Einteilungen kritisch diskutiert.

Sleep quality and associated factors among pregnant women attending antenatal care at Jimma Medical Center, Jimma, Southwest Ethiopia, 2020: cross-sectional study

BACKGROUND

Sleep is a natural physiological process vital for the physical and mental wellbeing of pregnant women and their fetuses. Even though poor sleep quality is a common problem among pregnant women, it is not studied in developing countries including Ethiopia. Therefore, this study was aimed to assess the poor sleep quality and associated factors among pregnant women attending antenatal care at Jimma medical center, Jimma, Southwest Ethiopia, 2020.

METHODS

A cross-sectional study design was conducted among 415 pregnant women at Jimma Medical Center (JMC). The study subjects were selected using a systematic random sampling technique. Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality using face-to-face interviews. SPSS version 25 was used to analyze data. Bivariate and multivariable logistic regressions were done to identify factors related to sleep quality. In multivariable logistic regression variables with a p-value less than 0.05 was considered significant and, adjusted OR (AOR) with 95% CI was used to present the strength of the association.

RESULTS

The prevalence of poor sleep quality among pregnant women was found to be 30.8% (95% CI (26.5, 35.2). In multivariable analysis, age ≥ 30 years old (AOR = 1.94;95%CI:1.03,3.66), Multigravida (AOR = 1.90;95%CI:1.90,3.32),depression (AOR = 4.26;95%CI:2.54,7.14),stress (AOR = 1.85;95%CI:1.20,3.02) were variables significantly associated with poor sleep quality.

CONCLUSION

This study found a high prevalence of poor sleep quality among pregnant women. Older age, gravidity, depression, and stress were associated with poor sleep quality. It is better to have routine sleep pattern screening and teach sleep hygiene practice for pregnant women.

Relationship between Sleep Problems and Self-Injury: A Systematic Review

Objective/Background: Previous studies suggested that sleep problems were related to non-suicidal self-injury. The current systematic review investigated more thoroughly this relationship.Methods: PubMED and Embase databases were searched. The keywords were "self-injury" OR "self-harm" OR "non-suicidal self-injury" OR "self-injurious behavior" OR "self-destructive behavior" OR "self-mutilation" AND "sleep problem" OR "sleep disturbance" OR insomnia OR nightmare OR "poor sleep quality" or "sleep disorders." A total of 16 studies were included in the present review.Results: The pattern of results indicated that sleep problems such as short sleep duration, sleep disturbances, and poor sleep quality were associated with non-suicidal self-injury. Additionally, emotional dysregulation, depression, and post-traumatic stress disorder appeared to mediate this relationship. Above all adolescents and young adults with sleep disruptions were at higher risk of non-suicidal self-injury.Conclusions:g Interventions to improve sleep quality and sleep duration might concomitantly decrease the risk of non-suicidal self-injury.