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

Subjective sleep quality in healthy young adults moderates associations of sensitivity to punishment and reward with functional connectivity of regions relevant for insomnia disorder

Chronic unhealthy sleeping behaviours are a major risk factor for the emergence of mood and anxiety disorders. Nevertheless, we are still lacking understanding why some individuals are more prone than others to affective dysregulation caused by sleep disruption. With preliminary evidence suggesting that brain activity during positive and negative emotional processing might play an important modulating role, we conducted whole-brain resting-state functional connectivity analyses in a large cohort of healthy young adults (N = 155). Using regions consistently affected in insomnia disorder as seeds, we investigated sleep quality-related neural connectivity patterns that were both insensitive and sensitive to the interactions with individual measures of reward and punishment processing, additionally assessing the links with indices of emotional health. The majority of the findings reflected interactions between sleep quality and reinforcement sensitivity, with the opposite associations reported in the good and poor sleepers. One of such connections, the coupling between precentral gyrus and posterior insula, was additionally negatively linked to trait anxiety, with the lowest connectivity values observed in poor sleepers with higher sensitivity to punishment. In turn, the only finding associated solely with sleep quality, i.e. coupling between subgenual anterior cingulate cortex and thalamus, was also related to the habitual use of emotion suppression strategies. As such, the present study provides evidence that reinforcement sensitivity plays an essential role in understanding the associations of poor sleep quality with brain connectivity and emotional health, hinting at a potential link that may help explain individual differences in susceptibility to sleep-related affective dysregulation.

Neural correlates of insomnia with depression and anxiety from a neuroimaging perspective: A systematic review

Insomnia affects a substantial proportion of the population and frequently co-occurs with mental illnesses including depression and anxiety. However, the neurobiological correlates of these disorders remain unclear. Here we review magnetic resonance imaging (MRI) studies assessing structural and functional brain associations with depressive and anxiety symptoms in insomnia disorder (ID; n = 38), insomnia symptoms in depressive and anxiety disorders (n = 14), and these symptoms in the general populations (n = 3). The studies on insomnia disorder consistently showed overlapping (salience network: insula and anterior cingulate cortex) and differential MRI correlation patterns between depressive (thalamus, orbitofrontal cortex and its associated functional connectivity) and anxiety (functional connectivity associated with default mode network) symptoms. The insula was also consistently identified as indicating the severity of insomnia symptoms in depressive disorder. In contrast, findings for other regions related to insomnia symptoms in both depressive and anxiety disorders were generally inconsistent across studies, partly due to variations in methods and patient cohorts. In the general population, brain regions in the default mode network provided a functional link between insomnia and depressive symptoms. These findings underscore both the shared and distinct neural correlates among depression, anxiety, and insomnia, providing potential avenues for the clinical management of these conditions.

The Future of Insomnia Research-There's Still Work to Be Done

Insomnia Disorder (ID) is a highly debilitating disorder affecting up to 10% of the general population. In recent years, the number of studies in this area has increased rapidly, resulting in a wealth of accumulated knowledge. ID is generally regarded as a hyperarousal disorder affecting cognitive, emotional, cortical and physiological domains. Nevertheless, there is still a significant lack of knowledge about the pathophysiology of ID. For example, the existence of insomnia subtypes is discussed, albeit no uniform definition has yet been found. Significant progress has been made in understanding the neurobiology of insomnia, which points to a dysfunction in emotion regulation. However, neuroimaging studies frequently have small sample sizes and allow only for limited causal conclusions. The assessment of sleep has been significantly influenced by the increasing availability of methods for ambulatory sleep measurement. While these methods enable sleep to be measured more cost-effectively than polysomnography, many devices lack sufficient empirical evidence of validity. In terms of insomnia treatment, cognitive behavioural therapy for insomnia (CBT-I) has been shown to be highly effective. However, the underlying mechanisms of CBT-I remain partially unclear, and the optimal sequence for applying the individual components, as well as the effectiveness of CBT-I in cases of comorbidity, remain open questions. Furthermore, many widely applied pharmacological treatment approaches are used off-label with only a limited empirical evidence base. This narrative review aims to summarise the current state of research on ID and attempts to outline a selection of the important future challenges in insomnia research.

Structural Imaging Measures of Cortical and Basal Ganglia Morphology in Insomnia

While insomnia disorder is associated with changes in the brain, results vary across studies and levels of severity; no consistent morphometric pattern has yet emerged. Prior large-scale genetic work has implicated specific cortical and subcortical regions in the pathophysiology of insomnia. The aim of the current study is to utilise surface-based morphometry tools to examine these specific regions, thereby offering new insights into the disorder from a genetically informed perspective. This study leveraged archival neuroimaging data from the University of Pittsburgh, analysing 58 individuals with DSM-IV-TR primary insomnia and 67 good sleepers. Using T1-weighted structural MRI scans, harmonised shape analysis protocols were applied for bilateral caudate, putamen and globus pallidus. In addition, cerebellar volumes, as well as anterior cingulate and rostral middle frontal cortical thickness measures were obtained. Linear models were then constructed to assess group differences in all regions, then correlation coefficients between brain values and scores from the Pittsburgh Sleep Quality Index (PSQI) from all participants were calculated. Results revealed individuals with insomnia exhibited significantly greater cortical thinning in anterior cingulate cortex, and inward shape deformation in the head of the right caudate compared to good sleepers. These findings reveal focal neurobiological abnormalities in insomnia that are in line with regions implicated in previous genetic work. The results may hold important implications for future research identifying biomarkers and mechanisms that contribute to the onset and course of insomnia in these areas.

Distinct Convergent Brain Alterations in Sleep Disorders and Sleep Deprivation: A Meta-Analysis

Importance

Sleep disorders have different etiologies yet share some nocturnal and daytime symptoms, suggesting common neurobiological substrates; healthy individuals undergoing experimental sleep deprivation also report analogous daytime symptoms. However, brain similarities and differences between long-term sleep disorders and short-term sleep deprivation are unclear.

Objective

To investigate the shared and specific neural correlates across sleep disorders and sleep deprivation.

Data Sources

PubMed, Web of Science, Embase, Scopus, and BrainMap were searched up to January 2024 to identify relevant structural and functional neuroimaging articles.

Study Selection

Whole-brain neuroimaging articles reporting voxel-based group differences between patients with different sleep disorders and healthy control participants or between total or partial sleep-deprived and well-rested individuals were included.

Data Extraction and Synthesis

Significant coordinates of group comparisons, their contrast direction (eg, patients < controls), and imaging modality were extracted. For each article, 2 raters independently evaluated eligibility and extracted data. Subsequently, several meta-analyses were performed with the revised activation likelihood estimation algorithm using P < .05 cluster-level familywise error correction.

Main Outcomes and Measures

Transdiagnostic regional brain alterations were identified across sleep disorders and among articles reporting sleep deprivation. Their associated behavioral functions and task-based or task-free connectivity patterns were explored using 2 independent datasets (BrainMap and the enhanced Nathan Kline Institute-Rockland Sample).

Results

A total of 231 articles (140 unique experiments, 3380 unique participants) were retrieved. The analysis across sleep disorders (n = 95 experiments) identified the subgenual anterior cingulate cortex (176 voxels, z score = 4.86), associated with reward, reasoning, and gustation, and the amygdala and hippocampus (130 voxels, z score = 4.00), associated with negative emotion processing, memory, and olfaction. Both clusters had positive functional connectivity with the default mode network. The right thalamus (153 voxels, z score = 5.21) emerged as a consistent regional alteration following sleep deprivation (n = 45 experiments). This cluster was associated with thermoregulation, action, and pain perception and showed positive functional connectivity with subcortical and (pre)motor regions. Subanalyses regarding the direction of alterations demonstrated that the subgenual anterior cingulate cortex exhibited decreased activation, connectivity, and/or volume, while the amygdala and hippocampus cluster and the thalamus cluster demonstrated increased activation, connectivity, and/or volume.

Conclusions and Relevance

Distinct convergent brain abnormalities were observed between long-term sleep disorders (probably reflecting shared symptoms) and short-term sleep deprivation.

Treatment of Insomnia With Traditional Chinese Medicine Presents a Promising Prospect

Insomnia, a prevalent sleep disorder, significantly impacts global health. While Western medications provide temporary relief, their risks of dependency and cognitive impairment have spurred the search for safer alternatives. Traditional Chinese Medicine (TCM) offers a promising approach to treating insomnia by focusing on harmonizing the balance of Yin and Yang and the functions of internal organs. This review explores recent research advances in TCM for insomnia treatment, integrating classical theories with modern scientific understanding of key pathological mechanisms, including neurotransmitter regulation (GABA, monoamines), immune-inflammatory responses, the HPA axis, and interactions with the gut microbiota. Growing clinical evidence supports the effectiveness of classical TCM prescriptions and treatments like acupuncture in improving sleep quality, particularly when combined with Western medications to enhance efficacy and reduce dependency. However, TCM also has its limitations. Future research directions should focus on modernizing TCM applications, addressing comorbidities associated with insomnia, exploring the role of gut microbiota, and optimizing medicinal and edible homologous products. By integrating traditional knowledge with cutting-edge technologies, TCM holds great potential for advancing personalized and effective insomnia treatments globally.

The Interplay Between the Sleep Slow Oscillation and Cerebrospinal Fluid: New Vistas for Insomnia Research

Insomnia disorder affects about 10% of the global population, representing a major health concern. Despite the availability of evidence-based treatments, the neurobiological mechanisms underpinning this disorder remain poorly understood. Recently, the investigation of the less than 1 Hz oscillations (commonly termed slow oscillations), a hallmark of slow wave sleep, has gained increased interest in research on insomnia. In this context, an intriguing perspective arises from the association between slow oscillations and metabolic waste clearance, an impaired process in individuals suffering from insomnia disorder. Indeed, the exploration of the relationships between cerebrospinal fluid dynamics and glymphatic system functions, which relate to brain metabolic clearance, and sleep slow oscillations may represent a promising avenue for future research in this field. This narrative review examines current knowledge about the intricate interplay among these mechanisms and their implications for insomnia disorder. Particular attention is given to the role of sleep slow oscillations in the clearance of metabolic waste during sleep, their coupling with cerebrospinal fluid oscillations, and the regulatory mechanisms underlying glymphatic function. The review emphasises the relevance of investigating sleep slow oscillations-related mechanisms in insomnia, intending to provide novel insights into the neurophysiological underpinnings of the disorder and contribute to more accurate diagnostic approaches. Furthermore, a deeper understanding of these mechanisms could pave the way for the development of innovative or adjunctive therapeutic strategies targeting sleep slow oscillations-related alterations in insomnia disorder.

Altered connection properties of the left dorsolateral superior frontal gyrus in de novo drug-naïve insomnia disorder

Background

Insomnia disorder (ID) is increasingly prevalent, posing significant risks to patients' physical and mental health. However, its neuropathological mechanisms remain unclear. Despite extensive research on ID using resting-state functional magnetic resonance imaging, a unified framework for describing its brain function alterations remains absent. Moreover, most prior studies have not fully accounted for the potential impact of medication on outcomes regarding enrollment criteria.

Methods

We recruited 22 ID and 22 healthy controls (HC), matched for age and gender. Patients with ID were never prescribed medications for sleep disorders before enrollment. We detected differences in voxel-wise degree centrality (DC) between the two groups and analyzed the correlation between altered DC values and insomnia severity. Additionally, we conducted receiver operating characteristic analysis to evaluate the diagnostic effectiveness of the altered DC values for ID.

Results

In ID patients, the weighted DC values of the left dorsolateral superior frontal gyrus (SFG) and the left supramarginal gyrus (SMG) were significantly lower than those of HC, with a notable negative correlation between the weighted DC values of the left dorsolateral SFG and PSQI scores. Receiver operating characteristic analysis showed that the weighted DC of the left dorsolateral SFG effectively differentiates between ID and HC, exhibiting high sensitivity and specificity.

Conclusion

This study offers new insights into brain dysfunction and the pathophysiology of ID through voxel-based DC measurements. The results indicate that altered DC properties of the left dorsolateral SFG might serve as a diagnostic marker for ID and a potential therapeutic target for brain function modulation.

Sleep and Arousal Hubs and Ferromagnetic Ultrafine Particulate Matter and Nanoparticle Motion Under Electromagnetic Fields: Neurodegeneration, Sleep Disorders, Orexinergic Neurons, and Air Pollution in Young Urbanites

Air pollution plays a key role in sleep disorders and neurodegeneration. Alzheimer's disease (AD), Parkinson's disease (PD), and/or transactive response DNA-binding protein TDP-43 neuropathology have been documented in children and young adult forensic autopsies in the metropolitan area of Mexico City (MMC), along with sleep disorders, cognitive deficits, and MRI brain atrophy in seemingly healthy young populations. Ultrafine particulate matter (UFPM) and industrial nanoparticles (NPs) reach urbanites' brains through nasal/olfactory, lung, gastrointestinal tract, and placental barriers. We documented Fe UFPM/NPs in neurovascular units, as well as lateral hypothalamic nucleus orexinergic neurons, thalamus, medullary, pontine, and mesencephalic reticular formation, and in pinealocytes. We quantified ferromagnetic materials in sleep and arousal brain hubs and examined their motion behavior to low magnetic fields in MMC brain autopsy samples from nine children and 25 adults with AD, PD, and TDP-43 neuropathology. Saturated isothermal remanent magnetization curves at 50-300 mT were associated with UFPM/NP accumulation in sleep/awake hubs and their motion associated with 30-50 µT (DC magnetic fields) exposure. Brain samples exposed to anthropogenic PM pollution were found to be sensitive to low magnetic fields, with motion behaviors that were potentially linked to the early development and progression of fatal neurodegenerative diseases and sleep disorders. Single-domain magnetic UFPM/NPs in the orexin system, as well as arousal, sleep, and autonomic regions, are key to neurodegeneration, behavioral and cognitive impairment, and sleep disorders. We need to identify children at higher risk and monitor environmental UFPM and NP emissions and exposures to magnetic fields. Ubiquitous ferrimagnetic particles and low magnetic field exposures are a threat to global brain health.

Neural network localization in Parkinson's disease with impulse control disorders

Background

There is a huge heterogeneity of magnetic resonance imaging findings in Parkinson's disease (PD) with impulse control disorders (ICDs) studies. Here, we hypothesized that brain regions identified by structural and functional imaging studies of PD with ICDs could be reconciled in a common network.

Methods

In this study, an initial systematic literature review was conducted to collect and evaluate whole-brain functional and structural magnetic resonance imaging studies related to PD with ICDs. We subsequently utilized the Human Connectome Project (HCP) dataset (n = 1,093) and a novel functional connectivity network mapping (FCNM) technique to identify a common brain network affected in PD with ICDs.

Results

A total of 19 studies with 25 contrasts, incorporating 345 individuals with PD and ICDs, and 787 individuals with PD without ICDs were included in the analysis. By using the HCP dataset and a novel FCNM technique, we ultimately identified that the aberrant neural networks predominantly involve the default mode network (middle and inferior temporal gyrus, anterior cingulate cortex, angular gyrus) and subcortical network (caudate nucleus).

Conclusion

This study suggests that the heterogeneous neuroimaging findings in PD with ICDs can be attributed to shared abnormalities in the default mode and subcortical networks. These dysfunctions are associated with impaired self-regulation, decision-making, and heightened impulsivity in PD with ICDs. Our findings integrate diverse neuroimaging results from previous studies, providing a clearer understanding of the neurobiological mechanisms underlying PD with ICDs at a network level.

Transcriptional signatures of cortical structural changes in chronic insomnia disorder

Chronic insomnia disorder (CID) is a multidimensional disease that may influence various levels of brain organization, spanning the macroscopic structural connectome to microscopic gene expression. However, the connection between genomic variations and morphological alterations in CID remains unclear. Here, we investigated brain structural changes in CID patients at the whole-brain level and whether these link to transcriptional characteristics. Brain structural data from 104 CID patients and 102 matched healthy controls (HC) were acquired to examine cortical structural alterations using morphometric similarity (MS) analysis. Partial least squares (PLS) regression and transcriptome data from the Allen Human Brain Atlas were used to extract genomes related to MS changes. Gene-category enrichment analysis (GCEA) was used to identify potential molecular mechanisms behind the observed structural changes. We found that CID patients exhibited MS reductions in the parietal and limbic regions, along with enhancements in the temporal and frontal regions compared to HCs (pFDR < .05). Subsequently, PLS and GCEA revealed that these MS alterations were spatially correlated with a set of genes, especially those significantly correlated with excitatory and inhibitory neurons and chronic neuroinflammation. This neuroimaging-transcriptomic study bridges the gap between cortical structural changes and the molecular mechanisms in CID patients, providing novel insight into the pathophysiology of insomnia and targeted treatments.

The altered hypothalamic network functional connectivity in chronic insomnia disorder and regulation effect of acupuncture: a randomized controlled neuroimaging study

BACKGROUND

The hypothalamus has been recognized as a core structure in the sleep-wake cycle. However, whether the neuroplasticity of the hypothalamus is involved in the acupuncture treatment of insomnia remains elusive.

METHODS

We recruited 42 patients with chronic insomnia disorder (CID) and 23 matched healthy controls (HCs), with CID patients randomly assigned to receive real acupuncture (RA) or sham acupuncture (SA) for four weeks. Insomnia severity was evaluated using the Pittsburgh Sleep Quality Index (PSQI) score, and the resting-state functional connectivity (rsFC) of the hypothalamus was assessed via functional magnetic resonance imaging (fMRI).

RESULTS

In the cross-sectional investigation, CID patients showed increased rsFC between the medial hypothalamus (MH) and left lateral orbital frontal cortex (LOFC), and bilateral medial orbital frontal cortex (MOFC) compared to HCs. In the longitudinal experiment, PSQI scores significantly decreased in the RA group (p = 0.03) but not in the SA group. Interestingly, the increased MH-LOFC connectivity was found to be reduced following RA treatment. In addition, the altered rsFC of MH-LOFC significantly correlated with clinical improvement in the RA group (r = -0.692, p = 0.006).

CONCLUSION

This randomized neuroimaging study provides preliminary evidence that acupuncture may improve insomnia symptoms by restoring circuits associated with hypothalamic subregions.

TRIAL REGISTRATION

This trial has been registered on the Chinese Clinical Trial Registry ( www.chictr.org.cn ) with the identifier (ChiCTR1800017092). Registered date: 11/07/2018.

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.

Insomnia-related brain functional correlates in first-episode drug-naïve major depressive disorder revealed by resting-state fMRI

Introduction

Insomnia is a common comorbidity symptom in major depressive disorder (MDD) patients. Abnormal brain activities have been observed in both MDD and insomnia patients, however, the central pathological mechanisms underlying the co-occurrence of insomnia in MDD patients are still unclear. This study aimed to explore the differences of spontaneous brain activity between MDD patients with and without insomnia, as well as patients with different level of insomnia.

Methods

A total of 88 first-episode drug-naïve MDD patients including 44 with insomnia (22 with high insomnia and 22 with low insomnia) and 44 without insomnia, as well as 44 healthy controls (HC), were enrolled in this study. The level of depression and insomnia were evaluated by HAMD-17, adjusted HAMD-17 and its sleep disturbance subscale in all subjects. Resting-state functional and structural magnetic resonance imaging data were acquired from all participants and then were preprocessed by the software of DPASF. Regional homogeneity (ReHo) values of brain regions were calculated by the software of REST and were compared. Finally, receiver operating characteristic (ROC) curves were conducted to determine the values of abnormal brain regions for identifying MDD patients with insomnia and evaluating the severity of insomnia.

Results

Analysis of variance showed that there were significant differences in ReHo values in the left middle frontal gyrus, left pallidum, right superior frontal gyrus, right medial superior frontal gyrus and right rectus gyrus among three groups. Compared with HC, MDD patients with insomnia showed increased ReHo values in the medial superior frontal gyrus, middle frontal gyrus, triangular inferior frontal gyrus, calcarine fissure and right medial superior frontal gyrus, medial orbital superior frontal gyrus, as well as decreased ReHo values in the left middle occipital gyrus, pallidum and right superior temporal gyrus, inferior temporal gyrus, middle cingulate gyrus, hippocampus, putamen. MDD patients without insomnia demonstrated increased ReHo values in the left middle frontal gyrus, orbital middle frontal gyrus, anterior cingulate gyrus and right triangular inferior frontal gyrus, as well as decreased ReHo values in the left rectus gyrus, postcentral gyrus and right rectus gyrus, fusiform gyrus, pallidum. In addition, MDD patients with insomnia had decreased ReHo values in the left insula when compared to those without insomnia. Moreover, MDD patients with high insomnia exhibited increased ReHo values in the right middle temporal gyrus, and decreased ReHo values in the left orbital superior frontal gyrus, lingual gyrus, right inferior parietal gyrus and postcentral gyrus compared to those with low insomnia. ROC analysis demonstrated that impaired brain region might be helpful for identifying MDD patients with insomnia and evaluating the severity of insomnia.

Conclusion

These findings suggested that MDD patients with insomnia had wider abnormalities of brain activities in the prefrontal-limbic circuits including increased activities in the prefrontal cortex, which might be the compensatory mechanism underlying insomnia in MDD. In addition, decreased activity of left insula might be associated with the occurrence of insomnia in MDD patients and decreased activities of the frontal-parietal network might cause more serious insomnia related to MDD.

The brain in chronic insomnia and anxiety disorder: a combined structural and functional fMRI study

Background

Chronic insomnia disorder (CID) is usually associated with Generalized Anxiety Disorder (GAD), which may change brain structure and function. However, the possible brain markers, imaging characteristics, and pathophysiology are unknown.

Objective

To look at the probable brain markers, imaging characteristics, and pathogenesis of CID in combination with GAD.

Methods

A total of 57 patients with CID concomitant GAD and 57 healthy controls (HC) were enrolled. Voxel-based morphometry (VBM) and functional connectivity (FC) were utilized to measure gray matter volume (GMV) and functional changes. Correlation analysis was utilized to identify relationships between brain changes and clinical characteristics.

Results

Patients had decreased GMV in the left cerebellum, right cerebellar peduncle, and left insula; increased FC between the left cerebellum and right angular gyrus, as well as between the left insula and anterior left cingulate gyrus; and decreased FC in several areas, including the left cerebellum with the middle left cingulate gyrus and the left insula with the left superior postcentral gyrus. These brain changes related to CID and GAD. These data could be used to identify relevant brain markers, imaging features, and to better understand the etiology.

Conclusion

The intensity of insomnia in patients was strongly related to the severity of anxiety. The lower GMV in the cerebellum could be interpreted as an imaging characteristic of CID. Reduced GMV in the insula, as well as aberrant function in the cingulate gyrus and prefrontal lobe, may contribute to the pathophysiology of CID and GAD. Abnormal function in the postcentral gyrus and angular gyrus may be associated with patients' clinical complaints.

Multimodal transformer graph convolution attention isomorphism network (MTCGAIN): a novel deep network for detection of insomnia disorder

Background

In clinic, the subjectivity of diagnosing insomnia disorder (ID) often leads to misdiagnosis or missed diagnosis, as ID may have the same symptoms as those of other health problems.

Methods

A novel deep network, the multimodal transformer graph convolution attention isomorphism network (MTGCAIN) is proposed in this study. In this network, graph convolution attention (GCA) is first employed to extract the graph features of brain connectivity and achieve good spatial interpretability. Second, the MTGCAIN comprehensively utilizes multiple brain network atlases and a multimodal transformer (MT) to facilitate coded information exchange between the atlases. In this way, MTGCAIN can be used to more effectively identify biomarkers and arrive at accurate diagnoses.

Results

The experimental results demonstrated that more accurate and objective diagnosis of ID can be achieved using the MTGCAIN. According to fivefold cross-validation, the accuracy reached 81.29% and the area under the receiver operating characteristic curve (AUC) reached 0.8760. A total of nine brain regions were detected as abnormal, namely right supplementary motor area (SMA.R), right temporal pole: superior temporal gyrus (TPOsup.R), left temporal pole: superior temporal gyrus (TPOsup.L), right superior frontal gyrus, dorsolateral (SFGdor.R), right middle temporal gyrus (MTG.R), left middle temporal gyrus (MTG.L), right inferior temporal gyrus (ITG.R), right median cingulate and paracingulate gyri (DCG.R), left median cingulate and paracingulate gyri (DCG.L).

Conclusions

The brain regions in the default mode network (DMN) of patients with ID show significant impairment (occupies four-ninths). In addition, the functional connectivity (FC) between the right middle occipital gyrus and inferior temporal gyrus (ITG) has an obvious correlation with comorbid anxiety (P=0.008) and depression (P=0.005) among patients with ID.

Investigating the shared genetic architecture between frailty and insomnia

Background

The epidemiological association between frailty and insomnia is well established, yet the presence of a common genetic etiology is still uncertain. Further exploration is needed to ascertain the causal relationship between frailty and insomnia.

Methods

Utilizing data obtained from genome-wide association studies (GWAS) summaries, we utilized the linkage disequilibrium score regression (LDSC) to determine the genetic correlation existing between frailty and insomnia. The determination of causality was achieved through the application of two-sample Mendelian randomization. We investigated the enrichment of single nucleotide polymorphism (SNP) at various tissue types utilizing stratified LD score regression (S-LDSC) and multimarker analysis of genome annotation (MAGMA). Common risk SNPs were identified using Multi-Trait Analysis of GWAS (MTAG) and Cross-Phenotype Association (CPASSOC). We further investigated the expression profiles of risk genes in tissues using Summary-data-based Mendelian randomization(SMR) based on pooled data, to explore potential functional genes.

Results

Our findings indicated a significant genetic correlation between frailty and insomnia, highlighting SNPs sharing risk (rs34290943, rs10865954), with a pronounced correlation in the localized genomic region 3p21.31. Partitioned genetic analysis revealed 24 functional elements significantly associated with both frailty and insomnia. Furthermore, mendelian randomization revealed a causal connection between frailty and insomnia. The genetic correlation between frailty and insomnia showed enrichment in 11 brain regions (S-LDSC) and 9 brain regions (MAGMA), where four functional genes (RMB6, MST1R, RF123, and FAM212A) were identified.

Conclusion

This study suggests the existence of a genetic correlation and common risk genes between frailty and insomnia, contributing to a deeper comprehension of their pathogenesis and assists in identifying potential therapeutic targets.