Alterations of Subcortical Brain Structures in Paradoxical and Psychophysiological Insomnia Disorder

Serum levels of neurotensin, pannexin-1, and sestrin-2 and the correlations with sleep quality or/and cognitive function in the patients with chronic insomnia disorder

Objectives

To examine serum concentrations of neurotensin, pannexin-1 and sestrin-2, and their correlations with subjective and objective sleep quality and cognitive function in the patients with chronic insomnia disorder (CID).

Methods

Sixty-five CID patients were enrolled continuously and fifty-six good sleepers in the same period were served as healthy controls (HCs). Serum levels of neurotensin, pannexin-1 and sestrin-2 were measured by enzyme-linked immunosorbent assays. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI) and polysomnography, and mood was evaluated by 17-item Hamilton Depression Rating Scale. General cognitive function was assessed with the Chinese-Beijing Version of Montreal Cognitive Assessment and spatial memory was evaluated by Blue Velvet Arena Test (BVAT).

Results

Relative to the HCs, the CID sufferers had higher levels of neurotensin (t=5.210, p<0.001) and pannexin-1 (Z=-4.169, p<0.001), and lower level of sestrin-2 (Z=-2.438, p=0.015). In terms of objective sleep measures, pannexin-1 was positively associated with total sleep time (r=0.562, p=0.002) and sleep efficiency (r=0.588, p=0.001), and negatively with wake time after sleep onset (r=-0.590, p=0.001) and wake time (r=-0.590, p=0.001); sestrin-2 was positively associated with percentage of rapid eye movement sleep (r=0.442, p=0.016) and negatively with non-rapid eye movement sleep stage 2 in the percentage (r=-0.394, p=0.034). Adjusted for sex, age and HAMD, pannexin-1 was still associated with the above objective sleep measures, but sestrin-2 was only negatively with wake time (r=-0.446, p=0.022). However, these biomarkers showed no significant correlations with subjective sleep quality (PSQI score). Serum concentrations of neurotensin and pannexin-1 were positively associated with the mean erroneous distance in the BVAT. Adjusted for sex, age and depression, neurotensin was negatively associated with MoCA score (r=-0.257, p=0.044), pannexin-1 was positively associated with the mean erroneous distance in the BVAT (r=0.270, p=0.033).

Conclusions

The CID patients had increased neurotensin and pannexin-1 and decreased sestrin-2 in the serum levels, indicating neuron dysfunction, which could be related to poor sleep quality and cognitive dysfunction measured objectively.

Brain structural correlates of subjective sleepiness and insomnia symptoms in shift workers

Background

Studies on the brain structures of shift workers are limited; thus, this cross-sectional study aimed to compare the brain structures and the brain structural correlates of subjective sleepiness and insomnia symptoms between shift workers and non-shift workers.

Methods

Shift workers (n = 63) and non-shift workers (n = 58) completed questionnaires assessing subjective sleepiness and insomnia symptoms. Cortical thickness, cortical surface area, and subcortical volumes were measured by magnetic resonance imaging. The brain morphometric measures were compared between the groups, and interaction analyses using the brain morphometric measures as the dependent variable were performed to test the interactions between the study group and measures of sleep disturbance (i.e., subjective sleepiness and insomnia symptoms).

Results

No differences in cortical thickness, cortical surface area, or subcortical volumes were detected between shift workers and non-shift workers. A single cluster in the left motor cortex showed a significant interaction between the study group and subjective sleepiness in the cortical surface area. The correlation between the left motor cortex surface area and the subjective sleepiness level was negative in shift workers and positive in non-shift workers. Significant interaction between the study group and insomnia symptoms was present for the left/right putamen volumes. The correlation between the left/right putamen volumes and insomnia symptom levels was positive in shift workers and negative in non-shift workers.

Conclusion

Left motor cortex surface area and bilateral putamen volumes were unique structural correlates of subjective sleepiness and insomnia symptoms in shift workers, respectively.

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.

Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes, with nine proteins and five metabolites replicated using independent exposure data. We found causal associations between accumbens volume and plasma protease c1 inhibitor as well as strong association between putamen volume and Agouti signaling protein. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

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.

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.

Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2,994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes. We found causal associations between amygdala volume and granzyme A as well as association between accumbens volume and plasma protease c1 inhibitor. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

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.

Sleep Dysfunction and Grey Matter Volume

PURPOSE OF REVIEW

With the voxel-based morphometry (VBM), structural imaging studies turned into new directions aiming to explore neurological disorders differently. This approach helps identify possible pathophysiological correlations between neuroanatomical grey matter (GM) structures in patients with sleep dysfunction. This article reviews recent findings on GM structure in various sleep disorders and possible causes of disturbed sleep and discusses the future perspectives.

RECENT FINDINGS

At present, research on the effect of GM volume changes in specific brain areas on the pathogenesis of sleep disturbances is incomplete. It remains unknown if the GM thickness reduction in patients with REM sleep behaviour disorder, obstructive sleep apnea, restless legs syndrome, and insomnia is due to complex disease presentation or direct response to disturbed sleep. Additionally, many VBM studies have yielded inconsistent results showing either reduction or increase in GM. The spatiotemporal complexity of whole-brain networks and state transitions during sleep and the role of GM changes increase new debates. Having multimodal data from large sample studies can help model sleep network dynamics in different disorders and provide novel data for possible therapeutic interventions.

PtNPs/Short MWCNT-PEDOT: PSS-Modified Microelectrode Array to Detect Neuronal Firing Patterns in the Dorsal Raphe Nucleus and Hippocampus of Insomnia Rats

Research on the intracerebral mechanism of insomnia induced by serotonin (5-HT) deficiency is indispensable. In order to explore the effect of 5-HT deficiency-induced insomnia on brain regions related to memory in rats, we designed and fabricated a microelectrode array that simultaneously detects the electrical activity of the dorsal raphe nucleus (DRN) and hippocampus in normal, insomnia and recovery rats in vivo. In the DRN and hippocampus of insomnia rats, our results showed that the spike amplitudes decreased by 40.16 and 57.92%, the spike repolarization slope decreased by 44.64 and 48.59%, and the spiking rate increased by 66.81 and 63.40%. On a mesoscopic scale, the increased firing rates of individual neurons led to an increased δ wave power. In the DRN and hippocampus of insomnia rats, the δ wave power increased by 57.57 and 67.75%. Furthermore, two segments’ δ wave slopes were also increased in two brain regions of the insomnia rats. Our findings suggest that 5-HT deficiency causes the hyperactivity of neurons in the hippocampus and DRN; the DRN’s firing rate and the hippocampal neuronal amplitude reflect insomnia in rats more effectively. Further studies on alleviating neurons affected by 5-HT deficiency and on achieving a highly effective treatment for insomnia by the microelectrode array are needed.

Network Mendelian randomization study: exploring the causal pathway from insomnia to type 2 diabetes

INTRODUCTION

Insomnia is a novel pathogen for type 2 diabetes mellitus (T2DM). However, mechanisms linking insomnia and T2DM are poorly understood. In this study, we apply a network Mendelian randomization (MR) framework to determine the causal association between insomnia and T2DM and identify the potential mediators, including overweight (body mass index (BMI), waist-to-hip ratio, and body fat percentage) and glycometabolism (HbA1c, fasting blood glucose, and fasting blood insulin).

RESEARCH DESIGN AND METHODS

We use the MR framework to detect effect estimates of the insomnia-T2DM, insomnia-mediator, and mediator-T2DM associations. A mediator between insomnia and T2DM is established if MR studies in all 3 steps prove causal associations.

RESULTS

In the Inverse variance weighted method, the results show that insomnia will increase the T2DM risk (OR 1.142; 95% CI 1.072 to 1.216; p=0.000), without heterogeneity nor horizontal pleiotropy, strongly suggesting that genetically predicted insomnia has a causal association with T2DM. Besides, our MR analysis provides strong evidence that insomnia is causally associated with BMI and body fat percentage. There is also suggestive evidence of an association between insomnia and the waist-to-hip ratio. At the same time, our results indicate that insomnia is not causally associated with glycometabolism. Higher BMI, waist-to-hip ratio, and body fat percentage levels are strongly associated with increased risk of T2DM.

CONCLUSIONS

Genetically predicted insomnia has a causal association with T2DM. Being overweight (especially BMI and body fat percentage) mediates the causal pathway from insomnia to T2DM.

The role of sleep disturbance and inflammation for spatial memory

Spatial memory is a brain function involved in multiple behaviors such as planning a route or recalling an object's location. The formation of spatial memory relies on the homeostasis of various biological systems, including healthy sleep and a well-functioning immune system. While sleep is thought to promote the stabilization and storage of spatial memories, considerable evidence shows that the immune system modulates neuronal processes underlying spatial memory such as hippocampal neuroplasticity, long-term potentiation, and neurogenesis. Conversely, when sleep is disturbed and/or states of heightened immune activation occur, hippocampal regulatory pathways are altered, which - on a behavioral level - may result in spatial memory impairments. In this Brief Review, I summarize how sleep and the immune system contribute to spatial memory processes. In addition, I present emerging evidence suggesting that sleep disturbance and inflammation might jointly impair spatial memory. Finally, potentials of integrated strategies that target sleep disturbance and inflammation to possibly mitigate risk for spatial memory impairment are discussed.

Asymmetric alterations of white matter integrity in patients with insomnia disorder

Despite the adverse consequences of insomnia disorder for both individuals and society, the underlying neurobiological processes are poorly understood. The purpose was to further understand the alterations of white matter tracts in patients with insomnia and their association with sleep variables and also to determine if diffusion tensor imaging measures would be a useful disease marker. Twenty-six patients with insomnia and 26 age-matched healthy volunteers underwent diffusion tensor imaging. We employed an automated probabilistic tractography analysis approach using TRActs Constrained by UnderLying Anatomy (TRACULA) to quantify diffusion measures in major white matter tracts. We found significantly increased fractional anisotropy in the right cingulum-angular bundle and uncinate fasciculus in patients group compared to controls. Moreover, the mean diffusivity and radial diffusivity were reduced in the right cingulum-angular bundle in patients group in comparison with controls. We also found significantly increased fractional anisotropy along the bilateral cingulum-angular bundle and right uncinate fasciculus in patients. Also, mean and radial diffusivity were reduced along the right cingulum-angular bundle in patients group compared to controls. There is a significant positive correlation between fractional anisotropy and Epworth Sleepiness Scale scores. Moreover, there are negative correlations between mean, radial and axial diffusivity and total sleep time and sleep efficiency and also positive correlations between mean, radial and axial diffusivity and duration of disease and Pittsburgh Sleep Quality Index scores. This study showed the importance of examining whole-tract and waypoint white matter integrity in insomnia disorder. We found asymmetric widespread white matter integrity changes in patients with insomnia.