Local dynamic spontaneous brain activity changes in first-episode, treatment-naïve patients with major depressive disorder and their associated gene expression profiles

Elucidating genetic and molecular basis of altered higher-order brain structure-function coupling in major depressive disorder

Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/β-hydrolase domain-containing 6 (ABHD6), β 1,3-N-acetylglucosaminyltransferase-9(β3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, β3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.

Gray matter volume and corresponding covariance connectivity are biomarkers for major depressive disorder

The major depressive disorder (MDD) is a common and severe mental disorder. To identify a reliable biomarker for MDD is important for early diagnosis and prevention. Given easy access and high reproducibility, the structural magnetic resonance imaging (sMRI) is an ideal method to identify the biomarker for depression. In this study, sMRI data of first episode, treatment-naïve 66 MDD patients and 54 sex-, age-, and education-matched healthy controls (HC) were used to identify the differences in gray matter volume (GMV), group-level, individual-level covariance connections. Finally, the abnormal GMV and individual covariance connections were applied to classify MDD from HC. MDD patients showed higher GMV in middle occipital gyrus (MOG) and precuneus (PCun), and higher structural covariance connections between MOG and PCun. In addition, the Allen Human Brain Atlas (AHBA) was applied and revealed the genetic basis for the changes of gray matter volume. Importantly, we reported that GMV in MOG, PCun and structural covariance connectivity between MOG and PCun are able to discriminate MDD from HC. Our results revealed structural underpinnings for MDD, which may contribute towards early discriminating for depression.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Alterations in dynamic regional homogeneity within default mode network in patients with thyroid-associated ophthalmopathy

Thyroid-associated ophthalmopathy (TAO) is a significant autoimmune eye disease known for causing exophthalmos and substantial optic nerve damage. Prior investigations have solely focused on static functional MRI (fMRI) scans of the brain in TAO patients, neglecting the assessment of temporal variations in local brain activity. This study aimed to characterize alterations in dynamic regional homogeneity (dReHo) in TAO patients and differentiate between TAO patients and healthy controls using support vector machine (SVM) classification. Thirty-two patients with TAO and 32 healthy controls underwent resting-state fMRI scans. We calculated dReHo using sliding-window methods to evaluate changes in regional brain activity and compared these findings between the two groups. Subsequently, we employed SVM, a machine learning algorithm, to investigate the potential use of dReHo maps as diagnostic markers for TAO. Compared to healthy controls, individuals with active TAO demonstrated significantly higher dReHo values in the right angular gyrus, left precuneus, right inferior parietal as well as the left superior parietal gyrus. The SVM model demonstrated an accuracy ranging from 65.62 to 68.75% in distinguishing between TAO patients and healthy controls based on dReHo variability in these identified brain regions, with an area under the curve of 0.70 to 0.76. TAO patients showed increased dReHo in default mode network-related brain regions. The accuracy of classifying TAO patients and healthy controls based on dReHo was notably high. These results offer new insights for investigating the pathogenesis and clinical diagnostic classification of individuals with TAO.

Comparision of spontaneous brain activity between hippocampal sclerosis and MRI-negative temporal lobe epilepsy

BACKGROUND

Hippocampal sclerosis (HS) is a prevalent cause of temporal lobe epilepsy (TLE). However, up to 30% of individuals with TLE present negative magnetic resonance imaging (MRI) findings. A comprehensive grasp of the similarities and differences in brain activity among distinct TLE subtypes holds significant clinical and scientific importance.

OBJECTIVE

To comprehensively examine the similarities and differences between TLE with HS (TLE-HS) and MRI-negative TLE (TLE-N) regarding static and dynamic abnormalities in spontaneous brain activity (SBA). Furthermore, we aimed to determine whether these alterations correlate with epilepsy duration and cognition, and to determine a potential differential diagnostic index for clinical utility.

METHODS

We measured 12 SBA metrics in 38 patients with TLE-HS, 51 with TLE-N, and 53 healthy volunteers. Voxel-wise analysis of variance (ANOVA) and post-hoc comparisons were employed to compare these metrics. The six static metrics included amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC), degree centrality (DC), and global signal correlation (GSCorr). Additionally, six corresponding dynamic metrics were assessed: dynamic ALFF (dALFF), dynamic fALFF (dfALFF), dynamic ReHo (dReHo), dynamic DC (dDC), dynamic VMHC (dVMHC), and dynamic GSCorr (dGSCorr). Receiver operating characteristic (ROC) curve analysis of abnormal indices was employed. Spearman correlation analyses were also conducted to examine the relationship between the abnormal indices, epilepsy duration and cognition scores.

RESULTS

Both TLE-HS and TLE-N presented as extensive neural network disorders, sharing similar patterns of SBA alterations. The regions with increased fALFF, dALFF, and dfALFF levels were predominantly observed in the mesial temporal lobe, thalamus, basal ganglia, pons, and cerebellum, forming a previously proposed mesial temporal epilepsy network. Conversely, decreased SBA metrics (fALFF, ReHo, dReHo, DC, GSCorr, and VMHC) consistently appeared in the lateral temporal lobe ipsilateral to the epileptic foci. Notably, SBA alterations were more obvious in patients with TLE-HS than in those with TLE-N. Additionally, patients with TLE-HS exhibited reduced VMHC in both mesial and lateral temporal lobes compared with patients with TLE-N, with the hippocampus displaying moderate discriminatory power (AUC = 0.759). Correlation analysis suggested that alterations in SBA indicators may be associated with epilepsy duration and cognitive scores.

CONCLUSIONS

The simultaneous use of static and dynamic SBA metrics provides evidence supporting the characterisation of both TLE-HS and TLE-N as complex network diseases, facilitating the exploration of mechanisms underlying epileptic activity and cognitive impairment. Overall, SBA abnormality patterns were generally similar between the TLE-HS and TLE-N groups, encompassing networks related to TLE and auditory and occipital visual functions. These changes were more pronounced in the TLE-HS group, particularly within the mesial and lateral temporal lobes.

Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study

AIMS

Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia.

METHODS

A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia.

RESULTS

The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity.

CONCLUSIONS

This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.

Abnormal large-scale brain functional network dynamics in social anxiety disorder

AIMS

Although static abnormalities of functional brain networks have been observed in patients with social anxiety disorder (SAD), the brain connectome dynamics at the macroscale network level remain obscure. We therefore used a multivariate data-driven method to search for dynamic functional network connectivity (dFNC) alterations in SAD.

METHODS

We conducted spatial independent component analysis, and used a sliding-window approach with a k-means clustering algorithm, to characterize the recurring states of brain resting-state networks; then state transition metrics and FNC strength in the different states were compared between SAD patients and healthy controls (HC), and the relationship to SAD clinical characteristics was explored.

RESULTS

Four distinct recurring states were identified. Compared with HC, SAD patients demonstrated higher fractional windows and mean dwelling time in the highest-frequency State 3, representing "widely weaker" FNC, but lower in States 2 and 4, representing "locally stronger" and "widely stronger" FNC, respectively. In State 1, representing "widely moderate" FNC, SAD patients showed decreased FNC mainly between the default mode network and the attention and perceptual networks. Some aberrant dFNC signatures correlated with illness duration.

CONCLUSION

These aberrant patterns of brain functional synchronization dynamics among large-scale resting-state networks may provide new insights into the neuro-functional underpinnings of SAD.

Abnormalities in static and dynamic intrinsic neural activity and neurotransmitters in first-episode OCD

BACKGROUND

Obsessive-compulsive disorder (OCD) is a disabling disorder in which the temporal variability of regional brain connectivity is not well understood. The aim of this study was to investigate alterations in static and dynamic intrinsic neural activity (INA) in first-episode OCD and whether these changes have the potential to reflect neurotransmitters.

METHODS

A total of 95 first-episode OCD patients and 106 matched healthy controls (HCs) were included in this study. Based on resting-state functional magnetic resonance imaging (rs-fMRI), the static and dynamic local connectivity coherence (calculated by static and dynamic regional homogeneity, sReHo and dReHo) were compared between the two groups. Furthermore, correlations between abnormal INA and PET- and SPECT-derived maps were performed to examine specific neurotransmitter system changes underlying INA abnormalities in OCD.

RESULTS

Compared with HCs, OCD showed decreased sReHo and dReHo values in left superior, middle temporal gyrus (STG/MTG), left Heschl gyrus (HES), left putamen, left insula, bilateral paracentral lobular (PCL), right postcentral gyrus (PoCG), right precentral gyrus (PreCG), left precuneus and right supplementary motor area (SMA). Decreased dReHo values were also found in left PoCG, left PreCG, left SMA and left middle cingulate cortex (MCC). Meanwhile, alterations in INA present in brain regions were correlated with dopamine system (D2, FDOPA), norepinephrine transporter (NAT) and the vesicular acetylcholine transporter (VAChT) maps.

CONCLUSION

Static and dynamic INA abnormalities exist in first-episode OCD, having the potential to reveal the molecular characteristics. The results help to further understand the pathophysiological mechanism and provide alternative therapeutic targets of OCD.

Twenty-five years of research on resting-state fMRI of major depressive disorder: A bibliometric analysis of hotspots, nodes, bursts, and trends

Major depressive disorder (MDD) is a debilitating mental health condition that poses significant risks and burdens. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a promising tool in investigating the neural mechanisms underlying MDD. However, a comprehensive bibliometric analysis of resting-state fMRI in MDD is currently lacking. Here, we aimed to thoroughly explore the trends and frontiers of resting-state fMRI in MDD research. The relevant publications were retrieved from the Web of Science database for the period between 1998 and 2022, and the CiteSpace software was employed to identify the influence of authors, institutions, countries/regions, and the latest research trends. A total of 1501 publications met the search criteria, revealing a gradual increase in the number of annual publications over the years. China contributed the largest publication output, accounting for the highest percentage among all countries. Particularly, the University of Electronic Science and Technology of China, Capital Medical University, and Harvard Medical School were identified as key institutions that have made substantial contributions to this growth. Neuroimage, Biological Psychiatry, Journal of Affective Disorders, and Proceedings of the National Academy of Sciences of the United States of America are among the influential journals in the field of resting-state fMRI research in MDD. Burst keywords analysis suggest the emerging research frontiers in this field are characterized by prominent keywords such as dynamic functional connectivity, cognitive control network, transcranial brain stimulation, and childhood trauma. Overall, our study provides a systematic overview into the historical development, current status, and future trends of resting-state fMRI in MDD, thus offering a useful guide for researchers to plan their future research.

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.

Altered intersubject functional variability of brain white-matter in major depressive disorder and its association with gene expression profiles

Major depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray-matter has been reported in MDD, the alterations to IVFC within white-matter (WM-IVFC) remain unknown. Based on the resting-state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM-IVFC between the two groups. We further assessed the meta-analytic cognitive functions related to the alterations. The discriminant WM-IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM-IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM-IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher-order functions. The discriminant WM-IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability-related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.

Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression

It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations. Enrichment analyses were conducted to characterize the biological functions and specific expression of identified genes, and Neurosynth decoding analysis was performed to examine the correlation between cognitive-related processes and VMHC alterations in schizophrenia. In the discovery and replication phases, patients with schizophrenia exhibited consistent VMHC changes compared to controls, which were correlated with a series of cognitive-related processes; meta-regression analysis revealed that illness duration was negatively correlated with VMHC abnormalities in the cerebellum and postcentral/precentral gyrus. The abnormal VMHC patterns were stably correlated with 1287 genes enriched for fundamental biological processes like regulation of cell communication, nervous system development, and cell communication. In addition, these genes were overexpressed in astrocytes and immune cells, enriched in extensive cortical regions and wide developmental time windows. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying VMHC alterations in patients with schizophrenia.

Exploring functional dysconnectivity in schizophrenia: alterations in eigenvector centrality mapping and insights into related genes from transcriptional profiles

Schizophrenia is a mental health disorder characterized by functional dysconnectivity. Eigenvector centrality mapping (ECM) has been employed to investigate alterations in functional connectivity in schizophrenia, yet the results lack consistency, and the genetic mechanisms underlying these changes remain unclear. In this study, whole-brain voxel-wise ECM analyses were conducted on resting-state functional magnetic resonance imaging data. A cohort of 91 patients with schizophrenia and 91 matched healthy controls were included during the discovery stage. Additionally, in the replication stage, 153 individuals with schizophrenia and 182 healthy individuals participated. Subsequently, a comprehensive analysis was performed using an independent transcriptional database derived from six postmortem healthy adult brains to explore potential genetic factors influencing the observed functional dysconnectivity, and to investigate the roles of identified genes in neural processes and pathways. The results revealed significant and reliable alterations in the ECM across multiple brain regions in schizophrenia. Specifically, there was a significant decrease in ECM in the bilateral superior and middle temporal gyrus, and an increase in the bilateral thalamus in both the discovery and replication stages. Furthermore, transcriptional analysis revealed 420 genes whose expression patterns were related to changes in ECM, and these genes were enriched mainly in biological processes associated with synaptic signaling and transmission. Together, this study enhances our knowledge of the neural processes and pathways involved in schizophrenia, shedding light on the genetic factors that may be linked to functional dysconnectivity in this disorder.

Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures

BACKGROUND

Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear.

OBJECTIVE

This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates.

METHODS

The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes.

RESULTS

Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development.

CONCLUSIONS

These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.

Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia

Deficit schizophrenia (DS) is a subtype of schizophrenia characterized by the primary and persistent negative symptoms. Previous studies have identified differences in brain functions between DS and non-deficit schizophrenia (NDS) patients. However, the genetic regulation features underlying these abnormal changes are still unknown. This study aimed to detect the altered patterns of functional connectivity (FC) in DS and NDS and investigate the gene expression profiles underlying these abnormal FC. The study recruited 82 DS patients, 96 NDS patients, and 124 healthy controls (CN). Voxel-based unbiased brain-wide association study was performed to reveal altered patterns of FC in DS and NDS patients. Machine learning techniques were used to access the utility of altered FC for diseases diagnosis. Weighted gene co-expression network analysis (WGCNA) was employed to explore the associations between altered FC and gene expression of 6 donated brains. Enrichment analysis was conducted to identify the genetic profiles, and the spatio-temporal expression patterns of the key genes were further explored. Comparing to CN, 23 and 20 brain regions with altered FC were identified in DS and NDS patients. The altered FC among these regions showed significant correlations with the SDS scores and exhibited high efficiency in disease classification. WGCNA revealed associations between DS/NDS-related gene expression and altered FC. Additionally, 22 overlapped genes, including 12 positive regulation genes and 10 negative regulation genes, were found between NDS and DS. Enrichment analyses demonstrated relationships between identified genes and significant pathways related to cellular response, neuro regulation, receptor binding, and channel activity. Spatial and temporal gene expression profiles of SCN1B showed the lowest expression at the initiation of embryonic development, while DPYSL3 exhibited rapid increased in the fetal. The present study revealed different altered patterns of FC in DS and NDS patients and highlighted the potential value of FC in disease classification. The associations between gene expression and neuroimaging provided insights into specific and common genetic regulation underlying these brain functional changes in DS and NDS, suggesting a potential genetic-imaging pathogenesis of schizophrenia.

Inflammation affects dynamic functional network connectivity pattern changes via plasma NFL in cognitive impairment patients

BACKGROUND

Plasma neurofilament light chain (NFL) is a biomarker of inflammation and neurodegenerative diseases such as Alzheimer's disease (AD). However, the underlying neural mechanisms by which NFL affects cognitive function remain unclear. In this study, we investigated the effects of inflammation on cognitive integrity in patients with cognitive impairment through the functional interaction of plasma NFL with large-scale brain networks.

METHODS

This study included 29 cognitively normal, 55 LowNFL patients, and 55 HighNFL patients. Group independent component analysis (ICA) was applied to the resting-state fMRI data, and 40 independent components (IC) were extracted for the whole brain. Next, the dynamic functional network connectivity (dFNC) of each subject was estimated using the sliding-window method and k-means clustering, and five dynamic functional states were identified. Finally, we applied mediation analysis to investigate the relationship between plasma NFL and dFNC indicators and cognitive scales.

RESULTS

The present study explored the dynamics of whole-brain FNC in controls and LowNFL and HighNFL patients and highlighted the temporal properties of dFNC states in relation to psychological scales. A potential mechanism for the association between dFNC indicators and NFL levels in cognitively impaired patients.

CONCLUSIONS

Our findings suggested the decreased ability of information processing and communication in the HighNFL group, which helps us to understand their abnormal cognitive functions clinically. Characteristic changes in the inflammation-coupled dynamic brain network may provide alternative biomarkers for the assessment of disease severity in cognitive impairment patients.

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.

Transcriptional signatures of the whole-brain voxel-wise resting-state functional network centrality alterations in schizophrenia

Neuroimaging studies have revealed that patients with schizophrenia exhibit disrupted resting-state functional connectivity. However, the inconsistent findings across these studies have hindered our comprehensive understanding of the functional connectivity changes associated with schizophrenia, and the molecular mechanisms associated with these alterations remain largely unclear. A quantitative meta-analysis was first conducted on 21 datasets, involving 1057 patients and 1186 healthy controls, to examine disrupted resting-state functional connectivity in schizophrenia, as measured by whole-brain voxel-wise functional network centrality (FNC). Subsequently, partial least squares regression analysis was employed to investigate the relationship between FNC changes and gene expression profiles obtained from the Allen Human Brain Atlas database. Finally, gene enrichment analysis was performed to unveil the biological significance of the altered FNC-related genes. Compared with healthy controls, patients with schizophrenia show consistently increased FNC in the right inferior parietal cortex extending to the supramarginal gyrus, angular gyrus, bilateral medial prefrontal cortex, and right dorsolateral prefrontal cortex, while decreased FNC in the bilateral insula, bilateral postcentral gyrus, and right inferior temporal gyrus. Meta-regression analysis revealed that increased FNC in the right inferior parietal cortex was positively correlated with clinical score. In addition, these observed functional connectivity changes were found to be spatially associated with the brain-wide expression of specific genes, which were enriched in diverse biological pathways and cell types. These findings highlight the aberrant functional connectivity observed in schizophrenia and its potential molecular underpinnings, providing valuable insights into the neuropathology of dysconnectivity associated with this disorder.

Transcriptional correlates of frequency-dependent brain functional activity associated with symptom severity in degenerative cervical myelopathy

BACKGROUND

Neuroimaging techniques provide insights into the brain abnormalities secondary to degenerative cervical myelopathy (DCM) and their association with neurological deficits. However, the neural correlates underlying the discrepancy between symptom severity and the degree of spinal cord compression, as well as the transcriptional correlates of these cortical abnormalities, remain unknown in DCM patients.

METHODS

In this cross-sectional study, which collected resting-state functional MRI (rs-fMRI) images and the Japanese Orthopedic Association (JOA) score, enrolled 104 participants (54 patients and 50 healthy controls). The frequency-dependent amplitude of low-frequency fluctuation (ALFF) was obtained for all participants. We investigated the ALFF differences between mild-symptom DCM patients and severe-symptom DCM patients while carefully matching the degree of compression between these two groups via both univariate comparison and searchlight classification for three frequency bands (e.g., Slow-4, Slow-5, and Full-band). Additionally, we identified genes associated with symptom severity in DCM patients by linking the spatial patterns of gene expression of Allen Human Brain Atlas and brain functional differences between mild symptom and severe symptom groups.

RESULTS

(1) We found that the frequency-specific brain activities within the sensorimotor network (SMN), visual network (VN), and default mode network (DMN) were associated with the varying degrees of functional impairment in DCM patients; (2) the frequency-specific brain activity within the SMN correlated with the functional recovery in patients with DCM; (3) a spatial correlation between the brain-wide expression of genes involved in neuronal migration and the brain functional activities associated with symptom severity was identified in DCM patients.

CONCLUSION

In conclusion, our study bridges gaps between genes, cell classes, biological processes, and brain functional correlates of DCM. While our findings are correlational in nature, they suggest that the neural activities of sensorimotor cortices in DCM are associated with the severity of symptoms and might be associated with neuronal migration within the brain.

Genes associated with spontaneous brain activity changes in clinically different patients with major depressive disorder: A transcription-neuroimaging association study

AIMS

The amplitude of low-frequency fluctuations (ALFF) of resting-state functional MRI signals is a reliable neuroimaging measure of spontaneous brain activity. Inconsistent ALFF alterations have been reported in major depressive disorder (MDD) possibly due to clinical heterogeneity. This study was designed to investigate clinically sensitive and insensitive genes associated with ALFF alterations in MDD and the potential mechanisms.

METHODS

Transcription-neuroimaging association analyses of case-control ALFF differences from two independent neuroimaging datasets with gene expression data from Allen Human Brain Atlas were performed to identify the two gene sets. Various enrichment analyses were conducted to characterize their preference in biological functions, cell types, temporal stages, and shared effects with other psychiatric disorders.

RESULTS

Compared with controls, first-episode and drug-naïve patients showed more extensive ALFF alterations than patients with varied clinical features. We identified 903 clinically sensitive genes and 633 clinically insensitive genes, and the former was enriched for genes with down-regulated expression in the cerebral cortex of MDD patients. Despite shared functions of cell communication, signaling, and transport, clinically sensitive genes were enriched for cell differentiation and development whereas clinically insensitive genes were for ion transport and synaptic signaling. Clinically sensitive genes showed enrichment for microglia and macrophage from childhood to young adulthood in contrast to clinically insensitive genes for neurons before early infancy. Clinically sensitive genes (15.2%) were less likely correlated with ALFF alterations in schizophrenia than clinically insensitive genes (66.8%), and both were not relevant to bipolar disorder and adult attention deficit and hyperactivity disorder based on a third independent neuroimaging dataset.

CONCLUSIONS

Present results provide novel insights into the molecular mechanisms of spontaneous brain activity changes in clinically different patients with MDD.

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.

Effects of home-based telerehabilitation on dynamic alterations in regional intrinsic neural activity and degree centrality in stroke patients

Objective

To explore the effects of home-based telerehabilitation (TR) on dynamic alterations in regional intrinsic neural activity and degree centrality in stroke patients by resting-state functional MRI (fMRI) methods.

Methods

The neuroimaging data of 52 stroke patients were analyzed. Dynamic regional spontaneous neural activity (dynamic amplitude of low-frequency fluctuations, dALFF; and dynamic regional homogeneity, dReHo) and dynamic degree centrality (dDC) were compared between the TR and conventional rehabilitation (CR) groups. A flexible factorial model was employed to investigate the expected effects.

Results

The patients in the TR group showed increased dALFF in the right precuneus and bilateral precentral gyrus (PreCG) and reduced dALFF in the right inferior parietal lobule by the analysis of main effects. Significant differences between groups were detected in the right precuneus, right fusiform gyrus and left middle frontal gyrus for dReHo and in the left cingulate gyrus, right middle temporal gyrus and left precuneus for dDC. A significant correlation was found in the TR group between the changed dALFF in the left PreCG and the changed Fugl-Meyer assessment (FMA) scores from baseline to postrehabilitation.

Conclusions

This study implied that home-based TR training can alter the patterns of dynamic spontaneous brain activity and functional connectivity in certain brain regions. The identification of key brain regions by neuroimaging indicators such as dynamic regional brain activity and degree centrality in the recovery process would provide a theoretical basis for noninvasive brain stimulation technology and strategies for formulating targeted rehabilitation programs for stroke patients with motor dysfunction.

Alterations in static and dynamic regional homogeneity in mesial temporal lobe epilepsy with and without initial precipitating injury

Objectives

Initial precipitating injury (IPI) such as febrile convulsion and intracranial infection will increase the susceptibility to epilepsy. It is still unknown if the functional deficits differ between mesial temporal lobe epilepsy with IPI (mTLE-IPI) and without IPI (mTLE-NO).

Methods

We recruited 25 mTLE-IPI patients, 35 mTLE-NO patients and 33 healthy controls (HC). Static regional homogeneity (sReHo) and dynamic regional homogeneity (dReHo) were then adopted to estimate the alterations of local neuronal activity. One-way analysis of variance was used to analyze the differences between the three groups in sReHo and dReHo. Then the results were utilized as masks for further between-group comparisons. Besides, correlation analyses were carried out to detect the potential relationships between abnormal regional homogeneity indicators and clinical characteristics.

Results

When compared with HC, the bilateral thalamus and the visual cortex in mTLE-IPI patients showed an increase in both sReHo and variability of dReHo. Besides, mTLE-IPI patients exhibited decreased sReHo in the right cerebellum crus1/crus2, inferior parietal lobule and temporal neocortex. mTLE-NO patients showed decreased sReHo and variability of dReHo in the bilateral temporal neocortex compared with HC. Increased sReHo and variability of dReHo were found in the bilateral visual cortex when mTLE-IPI patients was compared with mTLE-NO patients, as well as increased variability of dReHo in the left thalamus and decreased sReHo in the right dorsolateral prefrontal cortex. Additionally, we discovered a negative correlation between the national hospital seizure severity scale testing score and sReHo in the right cerebellum crus1 in mTLE-IPI patients.

Conclusion

According to the aforementioned findings, both mTLE-IPI and mTLE-NO patients had significant anomalies in local neuronal activity, although the functional deficits were much severer in mTLE-IPI patients. The use of sReHo and dReHo may provide a novel insight into the impact of the presence of IPI on the development of mTLE.

Functional connectivity alterations in reward-related circuits associated with non-suicidal self-injury behaviors in drug-naïve adolescents with depression

Non-suicidal self-injury (NSSI) behaviors are a major public health concern among adolescents with depression. Such behaviors may be associated with the reward system. However, the underlying mechanism in patients with depression and NSSI still remains unclear. A total of 56 drug-naïve adolescents with depression, including 23 patients with NSSI (the NSSI group) and 33 patients without NSSI (the nNSSI group), and 25 healthy controls (HCs) were recruited in this study. Seed-based functional connectivity (FC) was used to explore the NSSI-related FC alterations in the reward circuit. Correlation analysis was conducted between the altered FCs and clinical data. Compared with the nNSSI group, the NSSI group showed greater FC between left nucleus accumbens (NAcc) and right lingual gyrus and between right putamen accumbens and right angular gyrus (ANG). The NSSI group also had declined FC between right NAcc and left inferior cerebellum, between left cingulate gyrus (CG) and right ANG, between left CG and left middle temporal gyrus (MTG), and between right CG and bilateral MTG (voxel-wise p < 0.01, cluster-wise p < 0.05, Gaussian random field correction). The FC between right NAcc and left inferior cerebellum was found positively correlated with the score of addictive features of NSSI (r = 0.427, p = 0.042). Our findings indicated that the regions in the reward circuit with NSSI-related FC alterations included bilateral NAcc, right putamen and bilateral CG, which may provide new evidence on the neural mechanisms of NSSI behaviors in adolescents with depression.

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.

Structural covariances of prefrontal subregions selectively associate with dopamine-related gene coexpression and schizophrenia

Evidence highlights that dopamine (DA) system dysregulation and prefrontal cortex (PFC) dysfunction may underlie the pathophysiology of schizophrenia. However, the associations among DA genes, PFC morphometry, and schizophrenia have not yet been fully clarified. Based on the brain gene expression dataset from Allen Human Brain Atlas and structural magnetic resonance imaging data (NDIS = 1727, NREP = 408), we first identified 10 out of 22 PFC subregions whose gray matter volume (GMV) covariance profiles were reliably associated with their DA genes coexpression profiles, then four out of the identified 10 PFC subregions demonstrated abnormally increased GMV covariance with the hippocampus, insula, and medial frontal areas in schizophrenia patients (NCASE = 100; NCONTROL = 102). Moreover, based on a schizophrenia postmortem expression dataset, we found that the DA genes coexpression of schizophrenia was significantly reduced between the middle frontal gyrus and hippocampus, in which 21 DA genes showed significantly unsynchronized expression changes, and the 21 genes' brain expression were enriched in brain activity invoked by working memory, reward, speech production, and episodic memory. Our findings indicate the DA genes selectively regulate the structural covariance of PFC subregions by their coexpression profiles, which may underlie the disrupted GMV covariance and impaired cognitive functions in schizophrenia.

Spatiotemporal dynamics of functional connectivity and association with molecular architecture in schizophrenia

Schizophrenia is a self-disorder characterized by disrupted brain dynamics and architectures of multiple molecules. This study aims to explore spatiotemporal dynamics and its association with psychiatric symptoms. Resting-state functional magnetic resonance imaging data were collected from 98 patients with schizophrenia. Brain dynamics included the temporal and spatial variations in functional connectivity density and association with symptom scores were evaluated. Moreover, the spatial association between dynamics and receptors/transporters according to prior molecular imaging in healthy subjects was examined. Patients demonstrated decreased temporal variation and increased spatial variation in perceptual and attentional systems. However, increased temporal variation and decreased spatial variation were revealed in higher order networks and subcortical networks in patients. Specifically, spatial variation in perceptual and attentional systems was associated with symptom severity. Moreover, case-control differences were associated with dopamine, serotonin and mu-opioid receptor densities, serotonin reuptake transporter density, dopamine transporter density, and dopamine synthesis capacity. Therefore, this study implicates the abnormal dynamic interactions between the perceptual system and cortical core networks; in addition, the subcortical regions play a role in the dynamic interaction among the cortical regions in schizophrenia. These convergent findings support the importance of brain dynamics and emphasize the contribution of primary information processing to the pathological mechanism underlying schizophrenia.

Disrupted functional networks within white-matter served as neural features in adolescent patients with conduct disorder

BACKGROUND

Conduct disorder (CD) has been conceptualized as a psychiatric disorder associated with white-matter (WM) structural abnormalities. Although diffusion tensor imaging could identify WM structural architecture changes, it cannot characterize functional connectivity (FC) within WM. Few studies have focused on disentangling the WM dysfunctions in CD patients by using functional magnetic resonance imaging (fMRI).

METHODS

The resting-state fMRI data were first obtained from both adolescent CD and typically developing (TD) controls. A voxel-based clustering analysis was utilized to identify the large-scale WM FC networks. Then, we examined the disrupted WM network features in CD, and further investigated whether these features could predict the impulsive symptoms in CD using support vector regression prediction model.

RESULTS

We identified 11 WM functional networks. Compared with TDs, CD patients showed increased FCs between occipital network (ON) and superior temporal network (STN), between orbitofrontal network (OFN) and corona radiate network (CRN), as well as between deep network and CRN. Further, the disrupted FCs between ON and STN and between OFN and CRN were significantly negatively associated with non-planning impulsivity scores in CD. Moreover, the disrupted WM networks could be served as features to predict the motor impulsivity scores in CD.

CONCLUSIONS

Our results provided further support on the existence of WM functional networks and could extended our knowledge about the WM functional abnormalities related with emotional and perception processing in CD patients from the view of WM dysfunction.

Resting-state brain functional alterations and their genetic mechanisms in drug-naive first-episode psychosis

Extensive research has established the presence of resting-state brain functional damage in psychosis. However, the genetic mechanisms of such disease phenotype are yet to be unveiled. We investigated resting-state brain functional alterations in patients with drug-naive first-episode psychosis (DFP) by performing a neuroimaging meta-analysis of 8 original studies comprising 500 patients and 469 controls. Combined with the Allen Human Brain Atlas, we further conducted transcriptome-neuroimaging spatial correlations to identify genes whose expression levels were linked to brain functional alterations in DFP, followed by a range of gene functional characteristic analyses. Meta-analysis revealed a mixture of increased and decreased brain function in widespread areas including the default-mode, visual, motor, striatal, and cerebellar systems in DFP. Moreover, these brain functional alterations were spatially associated with the expression of 1662 genes, which were enriched for molecular functions, cellular components, and biological processes of the cerebral cortex, as well as psychiatric disorders including schizophrenia. Specific expression analyses demonstrated that these genes were specifically expressed in the brain tissue, in cortical neurons and immune cells, and during nearly all developmental periods. Concurrently, the genes could construct a protein-protein interaction network supported by hub genes and were linked to multiple behavioral domains including emotion, attention, perception, and motor. Our findings provide empirical evidence for the notion that brain functional damage in DFP involves a complex interaction of polygenes with various functional characteristics.

Shared and distinct patterns of dynamic functional connectivity variability of thalamo-cortical circuit in bipolar depression and major depressive disorder

Evidence has indicated abnormalities of thalamo-cortical functional connectivity (FC) in bipolar disorder during a depressive episode (BDD) and major depressive disorder (MDD). However, the dynamic FC (dFC) within this system is poorly understood. We explored the thalamo-cortical dFC pattern by dividing thalamus into 16 subregions and combining with a sliding-window approach. Correlation analysis was performed between altered dFC variability and clinical data. Classification analysis with a linear support vector machine model was conducted. Compared with healthy controls (HCs), both patients revealed increased dFC variability between thalamus subregions with hippocampus (HIP), angular gyrus and caudate, and only BDD showed increased dFC variability of the thalamus with superior frontal gyrus (SFG), HIP, insula, middle cingulate gyrus, and postcentral gyrus. Compared with MDD and HCs, only BDD exhibited enhanced dFC variability of the thalamus with SFG and superior temporal gyrus. Furthermore, the number of depressive episodes in MDD was significantly positively associated with altered dFC variability. Finally, the disrupted dFC variability could distinguish BDD from MDD with 83.44% classification accuracy. BDD and MDD shared common disrupted dFC variability in the thalamo-limbic and striatal-thalamic circuitries, whereas BDD exhibited more extensive and broader aberrant dFC variability, which may facilitate distinguish between these 2 mood disorders.

Evaluation of altered brain activity in type 2 diabetes using various indices of brain function: A resting-state functional magnetic resonance imaging study

Background

Type 2 diabetes mellitus (T2DM) has been identified as a risk factor that increases the rate of cognitive decline. Previous studies showed that patients with T2DM had brain function alterations based on a single index of resting-state functional magnetic resonance imaging (rs-fMRI). The present study aimed to explore spontaneous brain activity in patients with T2DM by comparing various rs-fMRI indices, and to determine the relationship between these changes and cognitive dysfunction.

Methods

A total of 52 patients with T2DM and age- and sex-matched control participants were included in this study. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC) values were calculated to represent the status of spontaneous neural activity. The Montreal Cognitive Assessment (MoCA) was used for the rapid evaluation of cognition in all subjects. Pearson correlation and mediation analyses were conducted to investigate the relationship between rs-fMRI indices and clinical parameters such as fasting glucose, disease duration, and MoCA.

Results

Patients with T2DM had alterations of concordant spontaneous brain activity in brain areas including the bilateral cerebellum posterior lobe, the left inferior temporal gyrus (ITG.L), the parahippocampal gyrus, and the left supplementary motor area (SMA.L). The indices were significantly correlated to each other in most of the detected brain areas. Positive correlations were observed between fasting glucose and neural activity in the surrounding areas of the left insula and the inferior frontal gyrus. MoCA scores were negatively correlated with the ReHo values extracted from the left anterior occipital lobe and the superior cerebellar cortex and were positively correlated with VMHC values extracted from the left caudate and the precentral gyrus (PreCG). No significant mediation effect of abnormal brain activity was found in the relationship between clinical parameters and MoCA scores.

Conclusion

The current study demonstrated the functional concordance of abnormal brain activities in patients with T2DM by comparing ALFF, ReHo, and VMHC measurements. Widespread abnormalities mainly involved in motor and sensory processing functions may provide insight into examining T2DM-related neurological pathophysiology.

Cerebral blood flow changes and their genetic mechanisms in major depressive disorder: a combined neuroimaging and transcriptome study

BACKGROUND

Extensive research has shown abnormal cerebral blood flow (CBF) in patients with major depressive disorder (MDD) that is a heritable disease. The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD.

METHODS

To achieve a more thorough characterization of CBF changes in MDD, we performed a comprehensive neuroimaging meta-analysis of previous literature as well as examined group CBF differences in an independent sample of 133 MDD patients and 133 controls. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD, followed by a set of gene functional feature analyses.

RESULTS

We found increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients. Moreover, these CBF changes were spatially associated with expression of 1532 genes, which were enriched for important molecular functions, biological processes, and cellular components of the cerebral cortex as well as several common mental disorders. Concurrently, these genes were specifically expressed in the brain tissue, in immune cells and neurons, and during nearly all developmental stages. Regarding behavioral relevance, these genes were associated with domains involving emotion and sensation. In addition, these genes could construct a protein-protein interaction network supported by 60 putative hub genes with functional significance.

CONCLUSIONS

Our findings suggest a cerebral perfusion redistribution in MDD, which may be a consequence of complex interactions of a wide range of genes with diverse functional features.

Genetic variations in the retrograde endocannabinoid signaling pathway in Chinese patients with major depressive disorder

Background

The retrograde endocannabinoid (eCB) pathway is closely associated with the etiology of major depressive disorder (MDD) at both pathophysiological and genetic levels. This study aimed to investigate the potential role of genetic mutations in the eCB pathway and underlying mechanisms in Han Chinese patients with MDD.

Methods

A total of 96 drug-naïve patients with first-episode MDD and 62 healthy controls (HCs) were recruited. Whole-exome sequencing was performed to identify the gene mutation profiles in patients with MDD. Results were filtered to focus on low-frequency variants and rare mutations (minor allele frequencies <0.05) related to depressive phenotypes. Enrichment analyses were performed for 146 selected genes to examine the pathways in which the most significant enrichment occurred. A protein-protein interaction (PPI) network analysis was performed to explore the biological functions of the eCB pathway. Finally, based on current literature, a preliminary analysis was conducted to explore the effect of genetic mutations on the function of this pathway.

Results

Our analysis identified 146 (15.02%) depression-related genetic mutations in patients with MDD when compared with HCs, and 37 of the mutations were enriched in the retrograde eCB signaling pathway. Seven hub genes in the eCB pathway were closely related to mitochondrial function, including Complex I genes (NDUFS4, NDUFV2, NDUFA2, NDUFA12, NDUFB11) and genes associated with protein (PARK7) and enzyme (DLD) function in the regulation of mitochondrial oxidative stress.

Conclusion

These results indicate that genetic mutations in the retrograde eCB pathway represent potential etiological factors associated with the pathogenesis of MDD.

Brain functional activity-based classification of autism spectrum disorder using an attention-based graph neural network combined with gene expression

Autism spectrum disorder (ASD) is a complex brain neurodevelopmental disorder related to brain activity and genetics. Most of the ASD diagnostic models perform feature selection at the group level without considering individualized information. Evidence has shown the unique topology of the individual brain has a fundamental impact on brain diseases. Thus, a data-constructing method fusing individual topological information and a corresponding classification model is crucial in ASD diagnosis and biomarker discovery. In this work, we trained an attention-based graph neural network (GNN) to perform the ASD diagnosis with the fusion of graph data. The results achieved an accuracy of 79.78%. Moreover, we found the model paid high attention to brain regions mainly involved in the social-brain circuit, default-mode network, and sensory perception network. Furthermore, by analyzing the covariation between functional magnetic resonance imaging data and gene expression, current studies detected several ASD-related genes (i.e. MUTYH, AADAT, and MAP2), and further revealed their links to image biomarkers. Our work demonstrated that the ASD diagnostic framework based on graph data and attention-based GNN could be an effective tool for ASD diagnosis. The identified functional features with high attention values may serve as imaging biomarkers for ASD.

Dynamic local metrics changes in patients with toothache: A resting-state functional magnetic resonance imaging study

Objective

To study the dynamic changes of local metrics in patients with toothache (TA, Toothache) in the resting state, in order to further understand the changes of central neural mechanism in patients with dental pain and its effect on cognition and emotion.

Methods

Thirty patients with TA and thirty matched healthy (HC) control volunteers were recruited, and resting-state functional magnetic resonance (rs-MRI) scans were performed on all subjects, and data were analyzed to compare group differences in three dynamic local indices: dynamic regional homogeneity (dReHO), dynamic low-frequency fluctuation amplitude (dALFF) and dynamic fractional low-frequency fluctuation amplitude (dfALFF). In addition, the association between dynamic local metrics in different brain regions of TA patients and scores on the Visual Analog Scale (VAS) and the Hospital Anxiety and Depression Scale (HADS) was investigated by Pearson correlation analysis.

Results

In this study, we found that The local metrics of TA patients changed with time Compared with the HC group, TA patients showed increased dReHo values in the left superior temporal gyrus, middle frontal gyrus, precentral gyrus, precuneus, angular gyrus, right superior frontal gyrus, middle temporal gyrus, postcentral gyrus and middle frontal gyrus, increased dALFF values in the right superior frontal gyrus, and increased dfALFF values in the right middle temporal gyrus, middle frontal gyrus and right superior occipital gyrus (p < 0.01, cluster level P < 0.05). Pearson correlation analysis showed that dReHo values of left precuneus and left angular gyrus were positively correlated with VAS scores in TA group. dReHo value of right posterior central gyrus was positively correlated with HADS score (P < 0.05).

Conclusion

There are differences in the patterns of neural activity changes in resting-state brain areas of TA patients, and the brain areas that undergo abnormal changes are mainly pain processing brain areas, emotion processing brain areas and pain cognitive modulation brain areas, which help to reveal their underlying neuropathological mechanisms. In the hope of further understanding its effects on cognition and emotion.

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.

Neurofilament light-associated connectivity in young-adult Huntington's disease is related to neuronal genes

Upregulation of functional network connectivity in the presence of structural degeneration is seen in the premanifest stages of Huntington's disease (preHD) 10-15 years from clinical diagnosis. However, whether widespread network connectivity changes are seen in gene carriers much further from onset has yet to be explored. We characterized functional network connectivity throughout the brain and related it to a measure of disease pathology burden (CSF neurofilament light, NfL) and measures of structural connectivity in asymptomatic gene carriers, on average 24 years from onset. We related these measurements to estimates of cortical and subcortical gene expression. We found no overall differences in functional (or structural) connectivity anywhere in the brain comparing control and preHD participants. However, increased functional connectivity, particularly between posterior cortical areas, correlated with increasing CSF NfL level in preHD participants. Using the Allen Human Brain Atlas and expression-weighted cell-type enrichment analysis, we demonstrated that this functional connectivity upregulation occurred in cortical regions associated with regional expression of genes specific to neuronal cells. This relationship was validated using single-nucleus RNAseq data from post-mortem Huntington's disease and control brains showing enrichment of neuronal-specific genes that are differentially expressed in Huntington's disease. Functional brain networks in asymptomatic preHD gene carriers very far from disease onset show evidence of upregulated connectivity correlating with increased disease burden. These changes occur among brain areas that show regional expression of genes specific to neuronal GABAergic and glutamatergic cells.

Dysregulated dynamic time-varying triple-network segregation in children with autism spectrum disorder

One of the remarkable characteristics of autism spectrum disorder (ASD) is the dysregulation of functional connectivity of the triple-network, which includes the salience network (SN), default mode network (DMN), and central executive network (CEN). However, there is little known about the segregation of the triple-network dynamics in ASD. This study used resting-state functional magnetic resonance imaging data including 105 ASD and 102 demographically-matched typical developing control (TC) children. We compared the dynamic time-varying triple-network segregation and triple-network functional connectivity states between ASD and TC groups, and examined the relationship between dynamic triple-network segregation alterations and clinical symptoms of ASD. The average dynamic network segregation value of the DMN with SN and the DMN with CEN in ASD was lower but the coefficient of variation (CV) of dynamic network segregation of the DMN with CEN was higher in ASD. Furthermore, partially reduced triple-network segregation associated with the DMN was found in connectivity states analysis of ASD. These abnormal average values and CV of dynamic network segregation predicted social communication deficits and restricted and repetitive behaviors in ASD. Our findings indicate abnormal dynamic time-varying triple-network segregation of ASD and highlight the crucial role of the triple-network in the neural mechanisms underlying ASD.

Aberrant static and dynamic functional connectivity of amygdala subregions in patients with major depressive disorder and childhood maltreatment

Major depressive disorder (MDD) with childhood maltreatment is a heterogeneous clinical phenotype of depression with prominent features of brain disconnectivity in areas linked to maltreatment-related emotion processing (e.g., the amygdala). However, static and dynamic alterations of functional connectivity in amygdala subregions have not been investigated in MDD with childhood maltreatment. Here, we explored whether amygdala subregions (i.e., medial amygdala [MeA] and lateral amygdala [LA]) exhibited static functional connectivity (sFC) and dynamic functional connectivity (dFC) disruption, and whether these disruptions were related to childhood maltreatment. We compared sFC and dFC patterns in MDD with childhood maltreatment (n = 48), MDD without childhood maltreatment (n = 30), healthy controls with childhood maltreatment (n = 57), and healthy controls without childhood maltreatment (n = 46). The bilateral MeA and LA were selected as the seeds in the FC analysis. The results revealed a functional connectivity disruption pattern in maltreated MDD patients, characterized by sFC and dFC abnormalities involving the MeA, LA, and theory of mind-related brain areas including the middle occipital area, middle frontal gyrus, superior medial frontal gyrus, angular gyrus, supplementary motor areas, middle temporal gyrus, middle cingulate gyrus, and calcarine gyrus. Significant correlations were detected between impaired dFC patterns and childhood maltreatment. Furthermore, the dFC disruption pattern served as a moderator in the relationship between sexual abuse and depression severity. Our findings revealed neurobiological features of childhood maltreatment, providing new evidence regarding vulnerability to psychiatric disorders.

Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study

Objective

The purpose of this study was to investigate the dynamic functional network connectivity (FNC) and its relationship with cognitive function in obstructive sleep apnea (OSA) patients from normal cognition (OSA-NC) to mild cognitive impairment (OSA-MCI).

Materials and methods

Eighty-two male OSA patients and 48 male healthy controls (HC) were included in this study. OSA patients were classified to OSA-MCI (n = 41) and OSA-NC (n = 41) based on cognitive assessments. The independent component analysis was used to determine resting-state functional networks. Then, a sliding-window approach was used to construct the dynamic FNC, and differences in temporal properties of dynamic FNC and functional connectivity strength were compared between OSA patients and the HC. Furthermore, the relationship between temporal properties and clinical assessments were analyzed in OSA patients.

Results

Two different connectivity states were identified, namely, State I with stronger connectivity and lower frequency, and State II with lower connectivity and relatively higher frequency. Compared to HC, OSA patients had a longer mean dwell time and higher fractional window in stronger connectivity State I, and opposite result were found in State II, which was mainly reflected in OSA-MCI patients. The number of transitions was an increasing trend and positively correlated with cognitive assessment in OSA-MCI patients. Compared with HC, OSA patients showed extensive abnormal functional connectivity in stronger connected State I and less reduced functional connectivity in lower connected State II, which were mainly located in the salience network, default mode network, and executive control network.

Conclusion

Our study found that OSA patients showed abnormal dynamic FNC properties, which was a continuous trend from HC, and OSA-NC to OSA-MCI, and OSA patients showed abnormal dynamic functional connectivity strength. The number of transformations was associated with cognitive impairment in OSA-MCI patients, which may provide new insights into the neural mechanisms in OSA patients.

Frequency-dependent white-matter functional network changes associated with cognitive deficits in subcortical vascular cognitive impairment

Vascular cognitive impairment (VCI) refers to all forms of cognitive decline associated with cerebrovascular diseases, in which white matter (WM) is highly vulnerable. Although previous studies have shown that blood oxygen level-dependent (BOLD) signals inside WM can effectively reflect neural activities, whether WM BOLD signal alterations are present and their roles underlying cognitive impairment in VCI remain largely unknown. In this study, 36 subcortical VCI (SVCI) patients and 36 healthy controls were enrolled to evaluate WM dysfunction. Specifically, fourteen distinct WM networks were identified from resting-state functional MRI using K-means clustering analysis. Subsequently, between-network functional connectivity (FC) and within-network BOLD signal amplitude of WM networks were calculated in three frequency bands (band A: 0.01-0.15 Hz, band B: 0.08-0.15 Hz, and band C: 0.01-0.08 Hz). Patients with SVCI manifested decreased FC mainly in bilateral parietal WM regions, forceps major, superior and inferior longitudinal fasciculi. These connections extensively linked with distinct WM networks and with gray-matter networks such as frontoparietal control, dorsal and ventral attention networks, which exhibited frequency-specific alterations in SVCI. Additionally, extensive amplitude reductions were found in SVCI, showing frequency-dependent properties in parietal, anterior corona radiate, pre/post central, superior and inferior longitudinal fasciculus networks. Furthermore, these decreased FC and amplitudes showed significant positive correlations with cognitive performances in SVCI, and high diagnostic performances for SVCI especially combining all bands. Our study indicated that VCI-related cognitive deficits were characterized by frequency-dependent WM functional abnormalities, which offered novel applicable neuromarkers for VCI.

Altered stability of brain functional architecture after sleep deprivation: A resting-state functional magnetic resonance imaging study

Background and aims

Resting-state functional magnetic resonance imaging (fMRI) studies using static and dynamic functional connectivity (FC) approaches have revealed brain dysfunction resulting from sleep deprivation (SD). The effects of SD on the stability of brain functional architecture remain unclear. This study investigated the functional stability (FS) changes induced by SD and its association with neurocognitive alterations.

Materials and methods

In this study, we recruited 24 healthy women. All participants underwent two sessions of resting-state fMRI scanning and neurocognitive assessment. The assessments included the Digit Symbol Test, Digit Span Test, Trail-Making Test (TMT), and Complex Figure Test (CFT). Participants completed one session under rested wakefulness (RW) and one session after SD for 24 h. To estimate dynamic FC, we used the sliding window approach; and then, to characterize the FS of each voxel, we measured dynamic FC concordance over time. We used a paired t-test to identify differences in FS between RW and SD. To examine the relationship between these changes in FS and alterations in neurocognitive performance, we conducted Spearman’s correlation analyses.

Results

SD affected the performance of the Digit Symbol Test, Digit Span Test, and CFT. Compared with RW, subjects with SD exhibited decreased FS in the bilateral anterior and posterior cingulate gyrus and medial frontal gyrus, right superior frontal gyrus, and cerebellum posterior lobe, while they exhibited increased FS in the bilateral precentral/postcentral gyrus and supplementary motor area, right parahippocampal gyrus and fusiform gyrus, left inferior occipital gyrus, and bilateral cerebellum anterior lobe. After SD, FS changes in the right parahippocampal gyrus and fusiform gyrus were correlated with altered performance in the Digit Symbol Test and CFT.

Conclusion

Our findings showed that the stability of the brain’s functional architecture could be altered by SD. This stability alteration may correspond to multiple neurocognitive domain changes.

Identification of suicidality in patients with major depressive disorder via dynamic functional network connectivity signatures and machine learning

Major depressive disorder (MDD) is a severe brain disease associated with a significant risk of suicide. Identification of suicidality is sometimes life-saving for MDD patients. We aimed to explore the use of dynamic functional network connectivity (dFNC) for suicidality detection in MDD patients. A total of 173 MDD patients, including 48 without suicide risk (NS), 74 with suicide ideation (SI), and 51 having attempted suicide (SA), participated in the present study. Thirty-eight healthy controls were also recruited for comparison. A sliding window approach was used to derive the dFNC, and the K-means clustering method was used to cluster the windowed dFNC. A linear support vector machine was used for classification, and leave-one-out cross-validation was performed for validation. Other machine learning methods were also used for comparison. MDD patients had widespread hypoconnectivity in both the strongly connected states (states 2 and 5) and the weakly connected state (state 4), while the dysfunctional connectivity within the weakly connected state (state 4) was mainly driven by suicidal attempts. Furthermore, dFNC matrices, especially the weakly connected state, could be used to distinguish MDD from healthy controls (area under curve [AUC] = 82), and even to identify suicidality in MDD patients (AUC = 78 for NS vs. SI, AUC = 88 for NS vs. SA, and AUC = 74 for SA vs. SI), with vision-related and default-related inter-network connectivity serving as important features. Thus, the dFNC abnormalities observed in this study might further improve our understanding of the neural substrates of suicidality in MDD patients.

Dynamic regional homogeneity alterations and cognitive impairment in patients with moderate and severe obstructive sleep apnea

Background and purpose

Previous studies have found that abnormal local spontaneous brain activity in patients with obstructive sleep apnea (OSA) was associated with cognitive impairment, and dynamic functional connections can capture the time changes of functional connections during magnetic resonance imaging acquisition. The purpose of this study was to investigate the dynamic characteristics of regional brain connectivity and its relationship with cognitive function in patients with OSA and to explore whether the dynamic changes can be used to distinguish them from healthy controls (HCs).

Methods

Seventy-nine moderate and severe male OSA patients without any treatment and 84 HCs with similar age and education were recruited, and clinical data and resting functional magnetic resonance imaging data were collected. The dynamic regional homogeneity (dReHo) was calculated using a sliding window technique, and a double-sample t-test was used to test the difference in the dReHo map between OSA patients and HCs. We explored the relationship between dReHo and clinical and cognitive function in OSA patients using Pearson correlation analysis. A support vector machine was used to classify the OSA patients and HCs based on abnormal dReHo.

Result

Compared with HCs, OSA patients exhibited higher dReHo values in the right medial frontal gyrus and significantly lower dReHo values in the right putamen, right superior temporal gyrus, right cingulate gyrus, left insula and left precuneus. The correlation analysis showed that the abnormal dReHo values in multiple brain regions in patients with OSA were significantly correlated with nadir oxygen saturation, the oxygen depletion index, sleep period time, and Montreal cognitive assessment score. The support vector machine classification accuracy based on the dReHo difference in brain regions was 81.60%, precision was 81.01%, sensitivity was 81.01%, specificity was 82.14%, and area under the curve was 0.89.

Conclusion

The results of this study suggested that there was abnormal dynamic regional spontaneous brain activity in patients with OSA, which was related to clinical and cognitive evaluation and can be used to distinguish OSA patients from HCs. The dReHo is a potential objective neuroimaging marker for patients with OSA that can further the understanding of the neuropathological mechanism of patients with OSA.

Aberrant Dynamic Functional Connectivity of Posterior Cingulate Cortex Subregions in Major Depressive Disorder With Suicidal Ideation

Accumulating evidence indicates the presence of structural and functional abnormalities of the posterior cingulate cortex (PCC) in patients with major depressive disorder (MDD) with suicidal ideation (SI). Nevertheless, the subregional-level dynamic functional connectivity (dFC) of the PCC has not been investigated in MDD with SI. We therefore sought to investigate the presence of aberrant dFC variability in PCC subregions in MDD patients with SI. We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 31 unmedicated MDD patients with SI (SI group), 56 unmedicated MDD patients without SI (NSI group), and 48 matched healthy control (HC) subjects. The sliding-window method was applied to characterize the whole-brain dFC of each PCC subregion [the ventral PCC (vPCC) and dorsal PCC (dPCC)]. In addition, we evaluated associations between clinical variables and the aberrant dFC variability of those brain regions showing significant between-group differences. Compared with HCS, the SI and the NSI groups exhibited higher dFC variability between the left dPCC and left fusiform gyrus and between the right vPCC and left inferior frontal gyrus (IFG). The SI group showed higher dFC variability between the left vPCC and left IFG than the NSI group. Furthermore, the dFC variability between the left vPCC and left IFG was positively correlated with Scale for Suicidal Ideation (SSI) score in patients with MDD (i.e., the SI and NSI groups). Our results indicate that aberrant dFC variability between the vPCC and IFG might provide a neural-network explanation for SI and may provide a potential target for future therapeutic interventions in MDD patients with SI.

Abnormal Dynamic Functional Connectivity in Patients With End-Stage Renal Disease

Dynamic functional connectivity (FC) analysis can capture time-varying properties of connectivity; however, studies focusing on dynamic FC in patients with end-stage renal disease (ESRD) are very limited. This is the first study to explore the dynamic aspects of whole-brain FC and topological properties in ESRD patients. Resting-state functional magnetic resonance imaging data were acquired from 100 ESRD patients [50 hemodialysis (HD) patients and 50 non-dialysis patients] and 64 healthy controls (HCs). Independent component analysis, a sliding-window approach and graph-theory methods were used to study the dynamic FC properties. The intrinsic brain FC were clustered into four configuration states. Compared with HCs, both patient groups spent longer time in State 3, in which decreased FC between subnetworks of the default mode network (DMN) and between the dorsal DMN and language network was observed in these patients, and a further reduction in FC between the DMN subnetworks was found in HD patients compared to non-dialysis patients. The number of transitions and the variability of global and local efficiency progressively decreased from that in HCs to that of non-dialysis patients to that of HD patients. The completion time of Trail Making Test A and Trail Making Test B positively correlated with the mean dwell time of State 3 and negatively correlated with the number of transitions in ESRD patients. Our findings suggest impaired functional flexibility of network connections and state-specific FC disruptions in patients with ESRD, which may underlie their cognitive deficits. HD may have an adverse effect on time-varying FC.

Altered Variability and Concordance of Dynamic Resting-State Functional Magnetic Resonance Imaging Indices in Patients With Major Depressive Disorder and Childhood Trauma

Childhood trauma is a non-specific risk factor for major depressive disorder (MDD). resting-state functional magnetic resonance imaging (R-fMRI) studies have demonstrated changes in regional brain activity in patients with MDD who experienced childhood trauma. However, previous studies have mainly focused on static characteristics of regional brain activity. This study aimed to determine the specific brain regions associated with MDD with childhood trauma by performing temporal dynamic analysis of R-fMRI data in three groups of patients: patients with childhood trauma-associated MDD (n = 48), patients without childhood trauma-associated MDD (n = 30), and healthy controls (n = 103). Dynamics and concordance of R-fMRI indices were calculated and analyzed. In patients with childhood trauma-associated MDD, a lower dynamic amplitude of low-frequency fluctuations was found in the left lingual gyrus, whereas a lower dynamic degree of centrality was observed in the right lingual gyrus and right calcarine cortex. Patients with childhood trauma-associated MDD showed a lower voxel-wise concordance in the left middle temporal and bilateral calcarine cortices. Moreover, group differences (depressed or not) significantly moderated the relationship between voxel-wise concordance in the right calcarine cortex and childhood trauma history. Overall, patients with childhood trauma-associated MDD demonstrated aberrant variability and concordance in intrinsic brain activity. These aberrances may be an underlying neurobiological mechanism that explains MDD from the perspective of temporal dynamics.

Abnormal regional spontaneous brain activities in white matter in patients with autism spectrum disorder

Previous studies have demonstrated patients with autism spectrum disorder (ASD) are accompanied by alterations of spontaneous brain activity in gray matter. However, whether the alterations of spontaneous brain activity exist in white matter remains largely unclear. In this study, 88 ASD patients and 87 typical controls (TCs) were included and regional homogeneity (ReHo) was calculated to characterize spontaneous brain activity in white matter. Voxel-wise two-sample t-tests were performed to investigate ReHo alterations, and cluster-level analyses were conducted to examine structural-functional coupling changes. Compared with TCs, the ASD group showed significantly decreased ReHo in the left superior corona radiata and left posterior limb of internal capsule, and decreased ReHo in the left anterior corona radiata with a trend level of significance. In addition, significantly weaker structural-functional coupling was observed in the left superior corona radiata and left posterior limb of internal capsule in ASD patients. Taken together, these findings highlighted abnormalities of white matter's regional spontaneous brain activity in ASD, which may provide new insights into the pathophysiological mechanisms of this disorder.

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

Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders that are highly heritable and are associated with impaired dynamic functional connectivity (DFC). However, the molecular mechanisms behind DFC alterations remain largely unknown. Eighty-eight patients with ASDs and 87 demographically matched typical controls (TCs) from the Autism Brain Imaging Data Exchange II database were included in this study. A seed-based sliding window approach was then performed to investigate the DFC changes in each of the 29 seeds in 10 classic resting-state functional networks and the whole brain. Subsequently, the relationships between DFC alterations in patients with ASDs and their symptom severity were assessed. Finally, transcription-neuroimaging association analyses were conducted to explore the molecular mechanisms of DFC disruptions in patients with ASDs. Compared with TCs, patients with ASDs showed significantly increased DFC between the right dorsolateral prefrontal cortex (DLPFC) and left fusiform/lingual gyrus, between the DLPFC and the superior temporal gyrus, between the right frontal eye field (FEF) and left middle frontal gyrus, between the FEF and the right angular gyrus, and between the left intraparietal sulcus and the right middle temporal gyrus. Moreover, significant relationships between DFC alterations and symptom severity were observed. Furthermore, the genes associated with DFC changes in ASDs were identified by performing gene-wise across-sample spatial correlation analysis between gene expression extracted from six donors’ brain of the Allen Human Brain Atlas and case-control DFC difference. In enrichment analysis, these genes were enriched for processes associated with synaptic signaling and voltage-gated ion channels and calcium pathways; also, these genes were highly expressed in autistic disorder, chronic alcoholic intoxication and several disorders related to depression. These results not only demonstrated higher DFC in patients with ASDs but also provided novel insight into the molecular mechanisms underlying these alterations.