Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders

Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) is a common disease that seriously endangers people's health, and is easily overlooked by both patients and clinicians due to its near-silent onset. Dynamic functional connectivity (DFC) is a new concept focusing on the dynamic features and patterns of brain networks that represents a powerful tool for gaining novel insight into neurological diseases. To assess alterations in DFC in CSVD patients, and the correlation of DFC with cognitive function. We enrolled 35 CSVD patients and 31 normal control subjects (NC). Resting-state functional MRI (rs-fMRI) with a sliding-window approach and k-means clustering based on independent component analysis (ICA) was used to evaluate DFC. The temporal properties of fractional windows and the mean dwell time in each state, as well as the number of transitions between each pair of DFC states, were calculated. Additionally, we assessed the functional connectivity (FC) strength of the dynamic states and the associations of altered neuroimaging measures with cognitive performance. A dynamic analysis of all included subjects suggested four distinct functional connectivity states. Compared with the NC group, the CSVD group had more fractional windows and longer mean dwell times in state 4 characterized by sparse FC both inter-network and intra-networks. Additionally, the CSVD group had a reduced number of windows and shorter mean dwell times compared to the NC group in state 3 characterized by highly positive FC between the somatomotor and visual networks, and negative FC in the basal ganglia and somatomotor and visual networks. The number of transitions between state 2 and state 3 and between state 3 and state 4 was significantly reduced in the CSVD group compared to the NC group. Moreover, there was a significant difference in the FC strength between the two groups, and the altered temporal properties of DFC were significantly related to cognitive performance. Our study indicated that CSVD is characterized by altered temporal properties in DFC that may be sensitive neuroimaging biomarkers for early disease identification. Further study of DFC alterations could help us to better understand the progressive dysfunction of networks in CSVD patients.

Coactivation pattern analysis reveals altered whole-brain functional transient dynamics in autism spectrum disorder

Recent studies on autism spectrum disorder (ASD) have identified recurring states dominated by similar coactivation pattern (CAP) and revealed associations between dysfunction in seed-based large-scale brain networks and clinical symptoms. However, the presence of abnormalities in moment-to-moment whole-brain dynamics in ASD remains uncertain. In this study, we employed seed-free CAP analysis to identify transient brain activity configurations and investigate dynamic abnormalities in ASD. We utilized a substantial multisite resting-state fMRI dataset consisting of 354 individuals with ASD and 446 healthy controls (HCs, from HC groups and 2). CAP were generated from a subgroup of all HC subjects (HC group 1) through temporal K-means clustering, identifying four CAPs. These four CAPs exhibited either the activation or inhibition of the default mode network (DMN) and were grouped into two pairs with opposing spatial CAPs. CAPs for HC group 2 and ASD were identified by their spatial similarity to those for HC group 1. Compared with individuals in HC group 2, those with ASD spent more time in CAPs involving the ventral attention network but less time in CAPs related to executive control and the dorsal attention network. Support vector machine analysis demonstrated that the aberrant dynamic characteristics of CAPs achieved an accuracy of 74.87% in multisite classification. In addition, we used whole-brain dynamics to predict symptom severity in ASD. Our findings revealed whole-brain dynamic functional abnormalities in ASD from a single transient perspective, emphasizing the importance of the DMN in abnormal dynamic functional activity in ASD and suggesting that temporally dynamic techniques offer novel insights into time-varying neural processes.

Altered static and dynamic functional network connectivity in primary angle-closure glaucoma patients

To explore altered patterns of static and dynamic functional brain network connectivity (sFNC and dFNC) in Primary angle-closure glaucoma (PACG) patients. Clinically confirmed 34 PACG patients and 33 age- and gender-matched healthy controls (HCs) underwent evaluation using T1 anatomical and functional MRI on a 3 T scanner. Independent component analysis, sliding window, and the K-means clustering method were employed to investigate the functional network connectivity (FNC) and temporal metrics based on eight resting-state networks. Differences in FNC and temporal metrics were identified and subsequently correlated with clinical variables. For sFNC, compared with HCs, PACG patients showed three decreased interactions, including SMN-AN, SMN-VN and VN-AN pairs. For dFNC, we derived four highly structured states of FC that occurred repeatedly between individual scans and subjects, and the results are highly congruent with sFNC. In addition, PACG patients had a decreased fraction of time in state 3 and negatively correlated with IOP (p < 0.05). PACG patients exhibit abnormalities in both sFNC and dFNC. The high degree of overlap between static and dynamic results suggests the stability of functional connectivity networks in PACG patients, which provide a new perspective to understand the neuropathological mechanisms of optic nerve damage in PACG patients.

Is cholesterol both the lock and key to abnormal transmembrane signals in Autism Spectrum Disorder?

Disturbances in cholesterol homeostasis have been associated with ASD. Lipid rafts are central in many transmembrane signaling pathways (including mTOR) and changes in raft cholesterol content affect their order function. Cholesterol levels are controlled by several mechanisms, including endoplasmic reticulum associated degradation (ERAD) of the rate limiting HMGCoA reductase. A new approach to increase cholesterol via temporary ERAD blockade using a benign bacterial toxin-derived competitor for the ERAD translocon is suggested.A new lock and key model for cholesterol/lipid raft dependent signaling is proposed in which the rafts provide both the afferent and efferent 'tumblers' across the membrane to allow 'lock and key' receptor transmembrane signals.

Disrupted functional connectivity of the habenula links psychomotor retardation and deficit of verbal fluency and working memory in late-life depression

BACKGROUND

Functional abnormalities of the habenula in patients with depression have been demonstrated in an increasing number of studies, and the habenula is involved in cognitive processing. However, whether patients with late-life depression (LLD) exhibit disrupted habenular functional connectivity (FC) and whether habenular FC mediates the relationship between depressive symptoms and cognitive impairment remain unclear.

METHODS

Overall, 127 patients with LLD and 75 healthy controls were recruited. The static and dynamic FC between the habenula and the whole brain was compared between LLD patients and healthy controls, and the relationships of habenular FC with depressive symptoms and cognitive impairment were explored by correlation and mediation analyses.

RESULTS

Compared with the controls, patients with LLD exhibited decreased static FC between the right habenula and bilateral inferior frontal gyrus (IFG); there was no significant difference in dynamic FC of the habenula between the two groups. Additionally, the decreased static FC between the right habenula and IFG was associated with more severe depressive symptoms (especially psychomotor retardation) and cognitive impairment (language, memory, and visuospatial skills). Last, static FC between the right habenula and left IFG partially mediated the relationship between depressive symptoms (especially psychomotor retardation) and cognitive impairment (verbal fluency and working memory).

CONCLUSIONS

Patients with LLD exhibited decreased static FC between the habenula and IFG but intact dynamic FC of the habenula. This decreased static FC mediated the relationship between depressive symptoms and cognitive impairment.

Characterizing the temporal dynamics of intrinsic brain activities in depressed adolescents with prior suicide attempts

Converging evidence has revealed disturbances in the corticostriatolimic system are associated with suicidal behaviors in adults with major depressive disorder. However, the neurobiological mechanism that confers suicidal vulnerability in depressed adolescents is largely unknown. A total of 86 depressed adolescents with and without prior suicide attempts (SA) and 47 healthy controls underwent resting-state functional imaging (R-fMRI) scans. The dynamic amplitude of low-frequency fluctuations (dALFF) was measured using sliding window approach. We identified SA-related alterations in dALFF variability primarily in the left middle temporal gyrus, inferior frontal gyrus, middle frontal gyrus (MFG), superior frontal gyrus (SFG), right SFG, supplementary motor area (SMA) and insula in depressed adolescents. Notably, dALFF variability in the left MFG and SMA was higher in depressed adolescents with recurrent suicide attempts than in those with a single suicide attempt. Moreover, dALFF variability was capable of generating better diagnostic and prediction models for suicidality than static ALFF. Our findings suggest that alterations in brain dynamics in regions involved in emotional processing, decision-making and response inhibition are associated with an increased risk of suicidal behaviors in depressed adolescents. Furthermore, dALFF variability could serve as a sensitive biomarker for revealing the neurobiological mechanisms underlying suicidal vulnerability.

Comprehensive elucidation of resting-state functional connectivity in anorexia nervosa by a multicenter cross-sectional study

BACKGROUND

Previous research on the changes in resting-state functional connectivity (rsFC) in anorexia nervosa (AN) has been limited by an insufficient sample size, which reduced the reliability of the results and made it difficult to set the whole brain as regions of interest (ROIs).

METHODS

We analyzed functional magnetic resonance imaging data from 114 female AN patients and 135 healthy controls (HC) and obtained self-reported psychological scales, including eating disorder examination questionnaire 6.0. One hundred sixty-four cortical, subcortical, cerebellar, and network parcellation regions were considered as ROIs. We calculated the ROI-to-ROI rsFCs and performed group comparisons.

RESULTS

Compared to HC, AN patients showed 12 stronger rsFCs mainly in regions containing dorsolateral prefrontal cortex (DLPFC), and 33 weaker rsFCs primarily in regions containing cerebellum, within temporal lobe, between posterior fusiform cortex and lateral part of visual network, and between anterior cingulate cortex (ACC) and thalamus (p < 0.01, false discovery rate [FDR] correction). Comparisons between AN subtypes showed that there were stronger rsFCs between right lingual gyrus and right supracalcarine cortex and between left temporal occipital fusiform cortex and medial part of visual network in the restricting type compared to the binge/purging type (p < 0.01, FDR correction).

CONCLUSION

Stronger rsFCs in regions containing mainly DLPFC, and weaker rsFCs in regions containing primarily cerebellum, within temporal lobe, between posterior fusiform cortex and lateral part of visual network, and between ACC and thalamus, may represent categorical diagnostic markers discriminating AN patients from HC.

Multilayer analysis of dynamic network reconfiguration in pediatric posttraumatic stress disorder

Neuroimage studies have reported functional connectome abnormalities in posttraumatic stress disorder (PTSD), especially in adults. However, these studies often treated the brain as a static network, and time-variance of connectome topology in pediatric posttraumatic stress disorder remain unclear. To explore case-control differences in dynamic connectome topology, resting-state functional magnetic resonance imaging data were acquired from 24 treatment-naïve non-comorbid pediatric posttraumatic stress disorder patients and 24 demographically matched trauma-exposed non-posttraumatic stress disorder controls. A graph-theoretic analysis was applied to construct time-varying modular structure of whole-brain networks by maximizing the multilayer modularity. Network switching rate at the global, subnetwork, and nodal levels were calculated and compared between posttraumatic stress disorder and trauma-exposed non-posttraumatic stress disorder groups, and their associations with posttraumatic stress disorder symptom severity and sex interactions were explored. At the global level, individuals with posttraumatic stress disorder exhibited significantly lower network switching rates compared to trauma-exposed non-posttraumatic stress disorder controls. This difference was mainly involved in default-mode and dorsal attention subnetworks, as well as in inferior temporal and parietal brain nodes. Posttraumatic stress disorder symptom severity was negatively correlated with switching rate in the global network and default mode network. No significant differences were observed in the interaction between diagnosis and sex/age. Pediatric posttraumatic stress disorder is associated with dynamic reconfiguration of brain networks, which may provide insights into the biological basis of this disorder.

Alterations of dynamic and static brain functional activities and integration in stroke patients

Objective

The study aimed to investigate the comprehensive characteristics of brain functional activity and integration in patients with subcortical stroke using dynamic and static analysis methods and to examine whether alterations in brain functional activity and integration were associated with clinical symptoms of patients.

Methods

Dynamic amplitude of low-frequency fluctuation (dALFF), static amplitude of low-frequency fluctuation (sALFF), dynamic degree centrality (dDC), and static degree centrality (sDC) were calculated for 19 patients with right subcortical stroke, 16 patients with left subcortical stroke, and 25 healthy controls (HC). Furthermore, correlation analysis was performed to investigate the relationships between changes in brain functional measurements of patients and clinical variables.

Results

Group comparison results showed that significantly decreased dALFF in the left angular (ANG_L) and right inferior parietal gyrus (IPG_R), decreased sALFF in the left precuneus (PCUN_L), and decreased sDC in the left crus II of cerebellar hemisphere (CERCRU2_L) and IPG_R, while significantly increased sDC in the right lobule X of cerebellar hemisphere (CER10_R) were detected in patients with right subcortical stroke relative to HC. Patients with left subcortical stroke showed significantly decreased sALFF in the left precuneus (PCUN_L) but increased sDC in the right hippocampus (HIP_R) compared with HC. Additionally, the altered sDC values in the CER10_R of patients with right subcortical stroke and in the HIP_R of patients with left subcortical stroke were associated with the severity of stroke and lower extremities motor function. A correlation was also found between the altered sALFF values in the PCUN_L of patients with left subcortical stroke and lower extremities motor function.

Conclusion

These findings suggest that time-varying brain activity analysis may supply complementary information for static brain activity analysis. Dynamic and static brain functional activity and integration analysis may contribute to a more comprehensive understanding of the underlying neuropathology of dysfunction in stroke patients.

Abnormal spontaneous brain activity in females with autism spectrum disorders

Objectives

To date, most studies on autism spectrum disorder (ASD) have focused on sample sets that were primarily or entirely composed of males; brain spontaneous activity changes in females remain unclear. The purpose of this study was to explore changes in the brain spontaneous neural activity in females with ASD.

Methods

In this study, resting-state functional magnetic resonance images (rs-fMRI) of 41 females with ASD and 41 typically developing (TD) controls were obtained from the ABDIE database. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) of the two groups were calculated to detect the regional brain activity. A two independent sample t-test was used to analyze differences between the ASD and TD groups and a p-value <0.05 was considered statistically significant after false discovery rate (FDR) correction. Pearson correlation analysis was conducted between social responsiveness scale (SRS) scores and the local activity of significantly different brain regions.

Results

Compared with the typically developing (TD) group, the values of ALFF and ReHo were significantly increased in the left superior temporal gyrus (STG), while the values of ReHo were significantly decreased in the left superior frontal gyrus (SFG), left middle occipital gyrus (MOG), bilateral superior parietal lobule (SPL), and bilateral precuneus in the females with ASD group. Correlation analysis showed that the ReHo of the right precuneus was positively correlated to the total SRS, social communication, and autistic mannerisms.

Conclusion

Spontaneous activity changes in females with ASD involved multiple brain regions and were related to clinical characteristics. Our results may provide some help for further exploring the neurobiological mechanism of females with ASD.

Abnormal dynamic functional network connectivity in patients with early-onset bipolar disorder

Objective

To explore the changes in dynamic functional brain network connectivity (dFNC) in patients with early-onset bipolar disorder (BD).

Methods

Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 39 patients with early-onset BD and 22 healthy controls (HCs). Four repeated and stable dFNC states were characterised by independent component analysis (ICA), sliding time windows and k-means clustering, and three dFNC temporal metrics (fraction of time, mean dwell time and number of transitions) were obtained. The dFNC temporal metrics and the differences in dFNC between the two groups in different states were evaluated, and the correlations between the differential dFNC metrics and neuropsychological scores were analysed.

Results

The dFNC analysis showed four connected patterns in all subjects. Compared with the HCs, the dFNC patterns of early-onset BD were significantly altered in all four states, mainly involving impaired cognitive and perceptual networks. In addition, early-onset BD patients had a decreased fraction of time and mean dwell time in state 2 and an increased mean dwell time in state 3 (p < 0.05). The mean dwell time in state 3 of BD showed a positive correlation trend with the HAMA score (r = 0.4049, p = 0.0237 × 3 > 0.05 after Bonferroni correction).

Conclusion

Patients with early-onset BD had abnormal dynamic properties of brain functional network connectivity, suggesting that their dFNC was unstable, mainly manifesting as impaired coordination between cognitive and perceptual networks. This study provided a new imaging basis for the neuropathological study of emotional and cognitive deficits in early-onset BD.

Abnormal brain functional network dynamics in sleep-related hypermotor epilepsy

AIMS

This study aimed to use resting-state functional magnetic resonance imaging (rs-fMRI) to determine the temporal features of functional connectivity states and changes in connectivity strength in sleep-related hypermotor epilepsy (SHE).

METHODS

High-resolution T1 and rs-fMRI scanning were performed on all the subjects. We used a sliding-window approach to construct a dynamic functional connectivity (dFC) network. The k-means clustering method was performed to analyze specific FC states and related temporal properties. Finally, the connectivity strength between the components was analyzed using network-based statistics (NBS) analysis. The correlations between the abovementioned measures and disease duration were analyzed.

RESULTS

After k-means clustering, the SHE patients mainly exhibited two dFC states. The frequency of state 1 was higher, which was characterized by stronger connections within the networks; state 2 occurred at a relatively low frequency, characterized by stronger connections between networks. SHE patients had greater fractional time and a mean dwell time in state 2 and had a larger number of state transitions. The NBS results showed that SHE patients had increased connectivity strength between networks. None of the properties was correlated with illness duration among patients with SHE.

CONCLUSION

The patterns of dFC patterns may represent an adaptive and protective mode of the brain to deal with epileptic seizures.

Genetic influence on brain volume alterations related to self-reported childhood abuse

As an important predictor of adulthood psychopathology, self-reported childhood abuse appears heritable and is associated with brain abnormalities. However, the specific genetic mechanisms behind these brain alterations remain largely unknown. This study recruited young adults who reported different degrees of childhood abuse from the community. In order to fully understand the influence of genes on brain changes related to self-reported childhood abuse, various experiments were conducted in this study. Firstly, volume changes of gray matter and white matter related to childhood abuse were investigated by using advanced magnetic resonance imaging techniques. After sequencing the whole exons, we further investigated the relationship between polygenic risk score, brain volume alterations, and childhood abuse score. Furthermore, transcription-neuroimaging association analysis was used to identify risk genes whose expressions were associated with brain volume alterations. The gray matter volumes of left caudate and superior parietal lobule, and white matter volumes of left cerebellum and right temporal lobe-basal ganglia region were significantly correlated with the childhood abuse score. More importantly, brain volume changes mediated the influence of polygenic risk on self-reported childhood abuse. Additionally, transcription-neuroimaging association analysis reported 63 risk genes whose expression levels were significantly associated with childhood abuse-related brain volume changes. These genes are involved in multiple biological processes, such as nerve development, synaptic transmission, and cell construction. Combining data from multiple perspectives, our work provides evidence of brain abnormalities associated with childhood abuse, and further indicates that polygene genetic risk and risk gene expression may affect the occurrence of childhood abuse by brain regulation, which provides insights into the molecularpathology and neuromechanism of childhood adversity. Paying attention to the physical and mental health of high-risk children may be a fundamental way to prevent childhood abuse and promote lifelong mental health.