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Background: The high comorbidity and symptom overlap of generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and social anxiety disorder (SAD), has led to the study of their shared and disorder-specific neural substrates. However, the morphometric similarity network (MSN) differences among these disorders remain unknown. Methods: MSN derived from T1-weighted images in patients of GAD, PTSD, and SAD, and health controls (HC) using a Siemens 3T magnetic resonance imaging system. Covariance analysis and post hoc tests were used to investigate group differences. In addition, the relationship between MSN and clinical characteristics was analyzed. Results: Increased morphometric similarity (MS) between left bankssts (BA22, superior temporal cortex, STC) and right precentral gyrus, and decreased MS between left precentral gyrus and right cuneus_part1/part2, and between right rostral middle frontal cortex (rMFC) and right STC were common in GAD and PTSD relative to HC and SAD. Compared to the other three groups, SAD exhibited disorder-specific alterations of increased MS between right rMFC and right STC, and between left cuneus and right inferior parietal cortex. Additionally, increased regional MSN in left precentral gyrus was found in PTSD compared to HC and SAD. A mild positive correlation of the MS value between left bankssts and right precentral gyrus and the Hamilton Anxiety Rating Scale scores (uncorrected p = 0.041) was found in PTSD. Conclusions: Our study provides the first evidence for common and distinct brain MSN abnormalities underlying the pathophysiology of GAD, PTSD, and SAD, which may aid in differential diagnosis and determining potential disorder-specific intervention targets. [ABSTRACT FROM AUTHOR]

Differentiating between patients with bipolar disorder (BD) and major depressive disorder (MDD) is clinically challenging. This study aimed to explore the potential of radiomic textural features for discriminating BD and MDD. A total 253 subjects (114 patients with BD, 139 patients with MDD) with T1-weighted MRI data were recruited. Radiomics features and gray matter volume (GMV) features were extracted from each brain region. A novel high-level MSN_II feature method based on radiomic features was proposed. And a total of 21 MSN features (5 MSN_I and 16 MSN_II) based on different combinations of the 5 types of radiomic textural feature were calculated. Classification models were constructed using various combinations of MSNs or GMV, and their performance and stability was evaluated through 2000 repeated experiments. The model built with combined features (GMV and GMV + MSN_II_GLCM_GLSZM_NGTDM) showed the best classification performance (AUC = 0.896 ± 0.058, ACC = 0.831 ± 0.064) in the validation cohort. After MANOVA analysis and FDR correlation, the MSN_II_GLCM_GLSZM_NGTDM values in 4 regions (right rectus gyrus, right temporal pole: middle temporal gyrus, Vermis3 and Vermis10) showed significant difference between BD and MDD. The main limitation of this study is that the data is derived from a single center without an external independent test set. Incorporating the high-level MSN_II based on radiomics features can improve the classification performance compared to models solely relying on GMV features alone. This result implied the potential application of the proposed high level MSN method and radiomics textural features on the MDD and BD clinical studies. • A novel high-order MSN feature based on radiomic texture features was proposed. • The proposed feature can discriminate MDD patients from BD patients. • The proposed feature can enhance the performance of GMV-only classification models. • The proposed features identified four brain regions where MDD and BD differ. [ABSTRACT FROM AUTHOR]

Abstract Background Individuals who have experienced severe traumatic events are estimated to have a post-traumatic stress disorder (PTSD) prevalence rate ranging from 10 to 50%, while those not affected by trauma exposure are often considered to possess psychological resilience. However, the neural mechanisms underlying the development of PTSD, especially resilience after trauma, remain unclear. This study aims to investigate changes of cortical morphometric similarity network (MSN) in PTSD and trauma-exposed healthy individuals (TEHI), as well as the associated molecular alterations in gene expression, providing potential targets for the prevention and intervention of PTSD. Methods We recruited PTSD patients and TEHI who had experienced severe earthquakes, and healthy controls who had not experienced earthquakes. We identified alterations in the whole-brain MSN changes in PTSD and TEHI, and established associations between these changes and brain-wide gene expression patterns from the Allen Human Brain Atlas microarray dataset using partial least squares regression. Results At the neuroimaging level, we found not only trauma-susceptible changes in TEHI same as those in PTSD, but also unique neurobiological alterations to counteract the deleterious impact of severe trauma. We identified 1444 and 2214 genes transcriptionally related to MSN changes in PTSD and TEHI, respectively. Functional enrichment analysis of weighted gene expression for PTSD and TEHI revealed distinct enrichments in Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, gene expression profiles of astrocytes, excitatory neurons, and microglial cells are highly related to MSN abnormalities in PTSD. Conclusions The formation of resilience may be by an active compensatory process of the brain. The combination of macroscopic neuroimaging changes and microscopic human brain transcriptomics could offer a more direct and in-depth understanding of the pathogenesis of PTSD and psychological resilience, shedding light on new targets for the prevention and treatment of PTSD.

Background: Individuals who have experienced severe traumatic events are estimated to have a post-traumatic stress disorder (PTSD) prevalence rate ranging from 10 to 50%, while those not affected by trauma exposure are often considered to possess psychological resilience. However, the neural mechanisms underlying the development of PTSD, especially resilience after trauma, remain unclear. This study aims to investigate changes of cortical morphometric similarity network (MSN) in PTSD and trauma-exposed healthy individuals (TEHI), as well as the associated molecular alterations in gene expression, providing potential targets for the prevention and intervention of PTSD. Methods: We recruited PTSD patients and TEHI who had experienced severe earthquakes, and healthy controls who had not experienced earthquakes. We identified alterations in the whole-brain MSN changes in PTSD and TEHI, and established associations between these changes and brain-wide gene expression patterns from the Allen Human Brain Atlas microarray dataset using partial least squares regression. Results: At the neuroimaging level, we found not only trauma-susceptible changes in TEHI same as those in PTSD, but also unique neurobiological alterations to counteract the deleterious impact of severe trauma. We identified 1444 and 2214 genes transcriptionally related to MSN changes in PTSD and TEHI, respectively. Functional enrichment analysis of weighted gene expression for PTSD and TEHI revealed distinct enrichments in Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, gene expression profiles of astrocytes, excitatory neurons, and microglial cells are highly related to MSN abnormalities in PTSD. Conclusions: The formation of resilience may be by an active compensatory process of the brain. The combination of macroscopic neuroimaging changes and microscopic human brain transcriptomics could offer a more direct and in-depth understanding of the pathogenesis of PTSD and psychological resilience, shedding light on new targets for the prevention and treatment of PTSD. [ABSTRACT FROM AUTHOR]

Background: It has been demonstrated that progressive supranuclear palsy (PSP) correlates with structural abnormalities in several distinct regions of the brain. However, whether there are changes in the morphological similarity network (MSN) and the relationship between changes in brain structure and gene expression remain largely unknown. Methods: We used two independent cohorts (discovery dataset: PSP: 51, healthy controls (HC): 82; replication dataset: PSP: 53, HC: 55) for MSN analysis and comparing the longitudinal changes in the MSN of PSP. Then, we applied partial least squares regression to determine the relationships between changes in MSN and spatial transcriptional features and identified specific genes associated with MSN differences in PSP. We further investigated the biological processes enriched in PSP‐associated genes and the cellular characteristics of these genes, and finally, we performed an exploratory analysis of the relationship between MSN changes and neurotransmitter receptors. Results: We found that the MSN in PSP patients was mainly decreased in the frontal and temporal cortex but increased in the occipital cortical region. This difference is replicable. In longitudinal studies, MSN differences are mainly manifested in the frontal and parietal regions. Furthermore, the expression pattern associated with MSN changes in PSP involves genes implicated in astrocytes and excitatory and inhibitory neurons and is functionally enriched in neuron‐specific biological processes related to synaptic signaling. Finally, we found that the changes in MSN were mainly negatively correlated with the levels of serotonin, norepinephrine, and opioid receptors. Conclusions: These results have enhanced our understanding of the microscale genetic and cellular mechanisms responsible for large‐scale morphological abnormalities in PSP patients, suggesting potential targets for future therapeutic trials. [ABSTRACT FROM AUTHOR]

Background: The promoter variant rs17111237 in the CEP128 closely relates to radiotherapy (RT)‐related brain necrosis in nasopharyngeal carcinoma (NPC) patients. Purpose: To explore RT‐related dynamic alterations in brain morphology and their potential genetic mechanism, and to explore the modulatory effects of CEP128 genetic variants on RT‐related brain morphological alterations in NPC patients. Study Type: Prospective, longitudinal. Population: One hundred one patients with histopathologic ally‐proven NPC (age 41.64 ± 9.63, 46 male), analyzed at baseline (pre‐RT), 3‐months post‐RT and 6 months post‐RT, and 19 sex‐, age‐ and education‐matched healthy controls. Field Strength/Sequence: 3D gradient echo brain volume (3D‐BRAVO) and diffusion‐weighted single‐shot spin‐echo echo‐planar sequences at 3.0 T. Assessment: rs17111237 in CEP128 was detected by Sanger sequencing. Structural and diffusion images were processed with FreeSurfer and FSL. Morphometric similarity network (MSN) was constructed with nine cortical indices derived from structural and diffusion images. Statistical Tests: One‐way ANOVA, chi‐square test. Pearson's correlation analysis was conducted to measure the relationship between CEP128 gene‐expression level in human brain and MSN alterations. Repeated analysis of variance performed to assess group differences in MSN and the modulatory effects of the CEP128 gene within patients. Significance level: P < 0.05, false‐discovery rate correction. Results: RT‐related significant widespread MSN alterations were observed in the cortices of NPC patients. Notably, regional MSN alterations had a weak but significant negative correlation with the cortical pattern of CEP128 gene expression (r = −0.152). Furthermore, rs17111237 in the CEP128 had significant modulatory effects on the observed MSN alterations in NPC patients, with the modulatory effects being most obvious at 3 months post‐RT. Conclusions: MSN has potential to serve as a sensitive biomarker to detect RT‐related brain injury. Inter‐brain regional and inter‐patient variability of RT‐related brain injuries may be attributed to the cortical expression of the CEP128 gene and the modulatory effects of the promoter variant rs17111237 in CEP128. Evidence Level: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Abstract Background This study aimed to investigate the neuroanatomical subtypes among early-onset schizophrenia (EOS) patients by exploring the association between structural alterations and molecular mechanisms using a combined analysis of morphometric similarity network (MSN) changes and specific transcriptional expression patterns. Methods We recruited 206 subjects aged 7 to 17 years, including 100 EOS patients and 106 healthy controls (HC). Heterogeneity through discriminant analysis (HYDRA) was used to identify the EOS subtypes within the MSN strength. The differences in morphometric similarity between each EOS subtype and HC were compared. Furthermore, we examined the link between morphometric changes and brain-wide gene expression in different EOS subtypes using partial least squares regression (PLS) weight mapping, evaluated genetic commonalities with psychiatric disorders, identified functional enrichments of PLS-weighted genes, and assessed cellular transcriptional signatures. Results Two distinct MSN-based EOS subtypes were identified, each exhibiting different abnormal MSN strength and cognitive functions compared to HC. The PLS1 score mapping demonstrated anterior–posterior gradients of gene expression in EOS1, whereas inverse distributions were observed in EOS2 cohorts. Genetic commonalities were identified in autistic disorder and adult schizophrenia with EOS1 and inflammatory bowel diseases with EOS2 cohorts. The EOS1 PLS1- genes (Z

Background: This study aimed to investigate the neuroanatomical subtypes among early-onset schizophrenia (EOS) patients by exploring the association between structural alterations and molecular mechanisms using a combined analysis of morphometric similarity network (MSN) changes and specific transcriptional expression patterns. Methods: We recruited 206 subjects aged 7 to 17 years, including 100 EOS patients and 106 healthy controls (HC). Heterogeneity through discriminant analysis (HYDRA) was used to identify the EOS subtypes within the MSN strength. The differences in morphometric similarity between each EOS subtype and HC were compared. Furthermore, we examined the link between morphometric changes and brain-wide gene expression in different EOS subtypes using partial least squares regression (PLS) weight mapping, evaluated genetic commonalities with psychiatric disorders, identified functional enrichments of PLS-weighted genes, and assessed cellular transcriptional signatures. Results: Two distinct MSN-based EOS subtypes were identified, each exhibiting different abnormal MSN strength and cognitive functions compared to HC. The PLS1 score mapping demonstrated anterior–posterior gradients of gene expression in EOS1, whereas inverse distributions were observed in EOS2 cohorts. Genetic commonalities were identified in autistic disorder and adult schizophrenia with EOS1 and inflammatory bowel diseases with EOS2 cohorts. The EOS1 PLS1- genes (Z < -5) were significantly enriched in synaptic signaling-related functions, whereas EOS2 demonstrated enrichments in virtual infection-related pathways. Furthermore, the majority of observed associations with EOS1-specific MSN strength differences contributed to specific transcriptional changes in astrocytes and neurons. Conclusions: The findings of this study provide a comprehensive analysis of neuroanatomical subtypes in EOS, shedding light on the intricate relationships between macrostructural and molecular aspects of the EOS disease. [ABSTRACT FROM AUTHOR]

The development of the cerebral cortex during the fetal period is a complex yet well-coordinated process. MRI-based morphological brain network provides a powerful tool for describing this process at a network level. Due to the challenges of in-utero MRI acquisition and image processing, the fetal morphological brain network has not been established. In this study, utilizing high-resolution in-utero MRI data, we constructed an individual morphometric similarity network for each fetus based on multiple cortical features. The spatiotemporal development of morphological connections was described at the level of edge, node, and lobe, respectively. Based on graph theoretical method, the topology structure of fetal morphological network was characterized. Edge analysis demonstrated an increase of morphological dissimilarity between hemispheres with gestational age, especially for the parietal cortex. The limbic and parieto-occipital regions exhibited the most drastic changes of morphological connections at both the edge and node levels. Between- and within-lobe analysis illustrated that the limbic lobe became more similar to other lobes, while the parietal and occipital lobes became more dissimilar to other lobes. Graph theoretical analysis indicated that the small-world structure of the fetal morphological network appeared as early as 22 weeks and that the network topology exhibited an enhanced integration and reduced segregation during prenatal development. The findings obtained from the preterm-born neonates agreed well with those of the fetuses. In summary, this study fills a gap in prenatal morphological brain network research and provides a piece of important evidence for understanding the normal development of fetal brain connectome during the second-third trimester.

Due to the diversity of traumatic events, the diagnosis of Post-traumatic Stress Disorder is heterogeneous. The pathogenesis has been explored in the fields of brain imaging and genomics separately, but the results are inconsistent. Previous research evidenced that there existed structural differences between PTSD and healthy controls in multiple brain regions. This study further looked into the differences of brain structure in PTSD at the whole brain level and analyzed the difference-related genomes. The brain structure imaging data of 36 patients and 32 healthy controls were taken as morphological indexes. Partial least squares regression and transcriptome data were used to extract genomes related to structural differences. Additional data sets were used to study transcription characteristics of genome. Morphological differences were found in cingulate gyrus between patients and control group. Differentially expressed genes related to Morphometric similarity networks difference space were also observed. The obtained genes (i.e., RORA, PRKG1 and FKBP5) were proved to be related to the disorder with no significant correlation with other mental illnesses. In the subsequent cell type analysis, astrocytes, excitatory neurons and inhibitory neurons were evidenced to have the most significant correlation with these genes. This study found morphologically different brain regions related to PTSD. The related genome transcription analysis connects the structural differences and molecular mechanisms. [ABSTRACT FROM AUTHOR]

Aims: Generalised epilepsy is thought to involve distributed brain networks. However, the molecular and cellular factors that render different brain regions more vulnerable to epileptogenesis remain largely unknown. We aimed to investigate epilepsy-related morphometric similarity network (MSN) abnormalities at the macroscale level and their relationships with microscale gene expressions at the microscale level. Methods: We compared the MSN of genetic generalised epilepsy with generalised tonic-clonic seizure patients (GGE-GTCS, n = 101) to demographically matched healthy controls (HC, n = 150). Cortical MSNs were estimated by combining seven morphometric features derived from structural magnetic resonance imaging for each individual. Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen Human Brain Atlas. Results: GGE-GTCS patients exhibited decreased regional MSNs in primary motor, prefrontal and temporal regions and increases in occipital, insular and posterior cingulate cortices, when compared with the HC. These case-control neuroimaging differences were validated using split-half analyses and were not affected by medication or drug response effects. When assessing associations with gene expression, genes associated with GGE-GTCS-related MSN differences were enriched in several biological processes, including 'synapse organisation', 'neurotransmitter transport' pathways and excitatory/inhibitory neuronal cell types. Collectively, the GGE-GTCS-related cortical vulnerabilities were associated with chromosomes 4, 5, 11 and 16 and were dispersed bottom-up at the cellular, pathway and disease levels, which contributed to epileptogenesis, suggesting diverse neurobiologically relevant enrichments in GGE-GTCS. Conclusions: By bridging the gaps between transcriptional signatures and in vivo neuroimaging, we highlighted the importance of using MSN abnormalities of the human brain in GGE-GTCS patients to investigate disease-relevant genes and biological processes. [ABSTRACT FROM AUTHOR]

Insomnia disorder (ID) is a highly heterogeneous psychiatric disease, and the use of neuroanatomical data to objectively define biological subtypes is essential. We aimed to examine the neuroanatomical subtypes of ID by morphometric similarity network (MSN) and the association between MSN changes and specific transcriptional expression patterns. We recruited 144 IDs and 124 healthy controls (HC). We performed heterogeneity through discriminant analysis (HYDRA) and identified subtypes within the MSN strength. Differences in MSN between subtypes and HC were compared, and clinical behavioral differences were compared between subtypes. In addition, we investigated the association between MSN changes and brain gene expression in different ID subtypes using partial least squares regression to assess genetic commonalities in psychiatric disorders and further performed functional enrichment analyses. Two distinct subtypes of ID were identified, each exhibiting different MSN changes compared to HC. Furthermore, subtype 1 is characterized by objective short sleep, impaired cognitive function, and some relationships with major depressive disorder and autism spectrum disorder (ASD). In contrast, subtype 2 has normal objective sleep duration but subjectively reports poor sleep and is only related to ASD. The pathogenesis of subtype 1 may be related to genes that regulate sleep rhythms and sleep-wake cycles. In contrast, subtype 2 is more due to adverse emotion perception and regulation. Overall, these findings provide insights into the neuroanatomical subtypes of ID, elucidating the relationships between structural and molecular aspects of the relevant subtypes., (© 2025 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Background: Recurrent major depressive disorder (RDD) is increasingly understood to be associated with a 'disconnection' within the brain areas. But, the true understanding of cortical connectivities remains challenging. Morphometric similarity network (MSN) with multi-modal magnetic resonance imaging (MRI) could provide more information about cortical micro-architecture changes in individuals with RDD., Methods: Here, we integrated multi-modal features from T1-weighted imaging, diffusion tensor imaging (DTI), and inhomogeneous magnetization transfer imaging (ihMT) to construct MSN. We used graph theory to calculate topological changes in MSN and explore their relationship with the severity and recurrence. The topological properties of 42 RDD patients were compared with 56 age, sex, and education-matched healthy controls., Results: RDD subjects showed significantly decreased global efficiency, increased characteristic path length, reduced nodal efficiencies in the parietal lobe, subcortical area, and temporal lobe, increased betweenness centrality in the left supplementary motor area (SMA), decreased intra-modular connections in the parietal module and decreased inter-modular connections between the parietal and prefrontal modules. Notably, the global efficiency, characteristic path length, local efficiency of the right superior parietal gyrus, and inter-modular connections between the parietal and prefrontal modules were significantly associated with the number of depressive episodes. The betweenness centrality in SMA and the intra-modular connections in the parietal module showed a positive relationship with 17-item Hamilton Rating Scale for Depression (HAMD) scores., Conclusions: The altered topology of MSN may serve as potential underlying pathological mechanisms of RDD. The impaired information integration of the network, particularly the disconnection within the fronto-parietal network, may be associated with the recurrence of depression. The SMA and the fronto-parietal network may be related to the severity of depression., Competing Interests: Declaration of competing interest Competing Interests: all authors disclosed no relevant relationships., (Copyright © 2024. Published by Elsevier Ltd.)

Objectives: To explore the differences in the cortical morphometric similarity network (MSN) between COVID-19 survivors and healthy controls, and the correlation between these differences and behavioral features and transcriptional signatures. Materials & methods: 39 COVID-19 survivors and 39 age-, sex- and education years-matched healthy controls (HCs) were included. All participants underwent MRI and behavioral assessments (PCL-17, GAD-7, PHQ-9). MSN analysis was used to compute COVID-19 survivors vs. HCs differences across brain regions. Correlation analysis was used to determine the associations between regional MSN differences and behavioral assessments, and determine the spatial similarities between regional MSN differences and risk genes transcriptional activity. Results: COVID-19 survivors exhibited decreased regional MSN in insula, precuneus, transverse temporal, entorhinal, para-hippocampal, rostral middle frontal and supramarginal cortices, and increased regional MSN in pars triangularis, lateral orbitofrontal, superior frontal, superior parietal, postcentral, and inferior temporal cortices. Regional MSN value of lateral orbitofrontal cortex was positively associated with GAD-7 and PHQ-9 scores, and rostral middle frontal was negatively related to PHQ-9 scores. The analysis of spatial similarities showed that seven risk genes (MFGE8, MOB2, NUP62, PMPCA, SDSL, TMEM178B, and ZBTB11) were related to regional MSN values. Conclusion: The MSN differences were associated with behavioral and transcriptional signatures, early psychological counseling or intervention may be required to COVID-19 survivors. Our study provided a new insight into understanding the altered coordination of structure in COVID-19 and may offer a new endophenotype to further investigate the brain substrate.

Background The cerebral cortex is represented through multiple multilayer morphometric similarity networks to study their modular structures. The approach introduces a novel way for studying brain networks' metrics across individuals, and can quantify network properties usually not revealed using conventional network analyses. Methods A total of 8 combinations or types of morphometric similarity networks were constructed – 4 combinations of the inter-regional cortical features on 2 brain atlases. The networks' modular structures were investigated by identifying those modular interactions that stay consistent across the combinations of inter-regional morphometric features and individuals. Results The results provide evidence of the community structures as the property of (i) cortical lobar divisions, and also as (ii) the product of different combinations of morphometric features used for the construction of the multilayer representations of the cortex. For the first time, this study has mapped out flexible and inflexible morphometric similarity hubs, and evidence has been provided about variations of the modular network topology across the multilayers with age and IQ. Conclusions The results contribute to understanding of intra-regional characteristics in cortical interactions, which potentially can be used to map heterogeneous neurodegeneration patterns in diseased brains. [ABSTRACT FROM AUTHOR]

Abstract Childhood adversity may act as a stressor to produce a cascade of neurobiological effects that irreversibly alter neural development, setting the stage for developing psychopathology in adulthood. The catechol‐O‐methyltransferase (COMT) Val158Met polymorphism has received much attention as a candidate gene associated with environmental adversity, modifying risk for psychopathology. In this study, we aim to see how gene × brain × environment models give a more integrative understanding of brain modifications that contribute to predicting psychopathology related to childhood adversity. A large nonclinical sample of young adults completed Childhood Trauma Questionnaire (CTQ), behavioral scores, multimodal magnetic resonance imaging (MRI) scans, and genotyping. We utilized graph‐based connectivity analysis in morphometric similarity mapping and resting‐state functional MRI to investigate brain alterations. Relationships among COMT genotypes, CTQ score, imaging phenotypes, and behavioral scores were identified by multiple regression and mediation effect analysis. Significant main effect of CTQ score was found in anatomic connectivity of orbitofrontal cortex that was an outstanding mediator supporting the relationship between CTQ score and anxiety/harm‐avoiding personality. We also noted the main effect of childhood trauma on reorganization of functional connectivity within the language network. Additionally, we found genotype × CTQ score interactions on functional connectivity of the right frontoparietal network as well as anatomic connectivity of motor and limbic regions. Our data demonstrate childhood adversity and COMT genotypes are associated with abnormal brain connectivity, structurally and functionally. Early identification of individuals at risk, assessment of brain abnormality, and cognitive interventions may help to prevent or limit negative outcomes.

• The first study for the fetal morphological brain network based on high-resolution in-utero MRI. • The morphological dissimilarity between hemispheres increased with gestational age, especially in the parietal cortex. • The limbic and parieto-occipital regions exhibited the most drastic changes in morphological connections during prenatal development. • The small-world structure of fetal morphological brain network appeared as early as 22 weeks. • The network topology followed an enhanced integration and reduced segregation during the fetal period. The development of the cerebral cortex during the fetal period is a complex yet well-coordinated process. MRI-based morphological brain network provides a powerful tool for describing this process at a network level. Due to the challenges of in-utero MRI acquisition and image processing, the fetal morphological brain network has not been established. In this study, utilizing high-resolution in-utero MRI data, we constructed an individual morphometric similarity network for each fetus based on multiple cortical features. The spatiotemporal development of morphological connections was described at the level of edge, node, and lobe, respectively. Based on graph theoretical method, the topology structure of fetal morphological network was characterized. Edge analysis demonstrated an increase of morphological dissimilarity between hemispheres with gestational age, especially for the parietal cortex. The limbic and parieto-occipital regions exhibited the most drastic changes of morphological connections at both the edge and node levels. Between- and within-lobe analysis illustrated that the limbic lobe became more similar to other lobes, while the parietal and occipital lobes became more dissimilar to other lobes. Graph theoretical analysis indicated that the small-world structure of the fetal morphological network appeared as early as 22 weeks and that the network topology exhibited an enhanced integration and reduced segregation during prenatal development. The findings obtained from the preterm-born neonates agreed well with those of the fetuses. In summary, this study fills a gap in prenatal morphological brain network research and provides a piece of important evidence for understanding the normal development of fetal brain connectome during the second-third trimester. [ABSTRACT FROM AUTHOR]

Menstrually-related migraine (MM) is a primary migraine in women of reproductive age. The underlying neural mechanism of MM was still unclear. In this study, we aimed to reveal the case-control differences in network integration and segregation for the morphometric similarity network of MM. Thirty-six patients with MM and 29 healthy females were recruited and underwent MRI scanning. The morphometric features were extracted in each region to construct the single-subject interareal cortical connection using morphometric similarity. The network topology characteristics, in terms of integration and segregation, were analyzed. Our results revealed that, in the absence of morphology differences, disrupted cortical network integration was found in MM patients compared to controls. The patients with MM showed a decreased global efficiency and increased characteristic path length compared to healthy controls. Regional efficiency analysis revealed the decreased efficiency in the left precentral gyrus and bilateral superior temporal gyrus contributed to the decreased network integration. The increased nodal degree centrality in the right pars triangularis was positively associated with the attack frequency in MM. Our results suggested MM would reorganize the morphology in the pain-related brain regions and reduce the parallel information processing capacity of the brain., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Antipsychotic treatment has been conceived to alter brain connectivity, but it is unclear how the changes of network phenotypes relate to the underlying transcriptomics. Given DNA methylation (DNAm) may alter transcriptional levels, we further integrated an imaging-transcriptomic-epigenetic analysis to explore multi-omics treatment response biomarkers. Forty-two treatment-naive first-episode schizophrenia patients were scanned by TI weighted (T1W) imaging and DTI before and after 8-week risperidone monotherapy, and their peripheral blood genomic DNAm values were examined in parallel with MRI scanning. Morphometric similarity network (MSN) quantified with DTI and T1W data were used as a marker of treatment-related alterations in interareal cortical connectivity. We utilized partial least squares (PLS) to examine spatial associations between treatment-related MSN variations and cortical transcriptomic data obtained from the Allen Human Brain Atlas. Longitudinal MSN alterations were related to treatment response on cognitive function and general psychopathology symptoms, while DNAm values of 59 PLS1 genes were on negative and positive symptoms. Virtual-histology transcriptomic analysis linked the MSN alterations with the neurobiological, cellular and metabolic pathways or processes, and assigned MSN-related genes to multiple cell types, specifying neurons and glial cells as contributing most to the transcriptomic associations of longitudinal changes in MSN. We firstly reveal how brain-wide transcriptional levels and cell classes capture molecularly validated cortical connectivity alterations after antipsychotic treatment. Our findings represent a vital step towards the exploration of treatment response biomarkers on the basis of multiple omics rather than a single omics type as a strategy for advancing precise care. • The neural network MSN and DNAm modalities may be complementary in predicting treatment response. • Virtual histology study identified specific cell classes enriched for the treatment-related MSN variations. • This study represents a vital step to advance precise and personalized care. [ABSTRACT FROM AUTHOR]

Aims: Generalised epilepsy is thought to involve distributed brain networks. However, the molecular and cellular factors that render different brain regions more vulnerable to epileptogenesis remain largely unknown. We aimed to investigate epilepsy-related morphometric similarity network (MSN) abnormalities at the macroscale level and their relationships with microscale gene expressions at the microscale level., Methods: We compared the MSN of genetic generalised epilepsy with generalised tonic-clonic seizure patients (GGE-GTCS, n = 101) to demographically matched healthy controls (HC, n = 150). Cortical MSNs were estimated by combining seven morphometric features derived from structural magnetic resonance imaging for each individual. Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen Human Brain Atlas., Results: GGE-GTCS patients exhibited decreased regional MSNs in primary motor, prefrontal and temporal regions and increases in occipital, insular and posterior cingulate cortices, when compared with the HC. These case-control neuroimaging differences were validated using split-half analyses and were not affected by medication or drug response effects. When assessing associations with gene expression, genes associated with GGE-GTCS-related MSN differences were enriched in several biological processes, including 'synapse organisation', 'neurotransmitter transport' pathways and excitatory/inhibitory neuronal cell types. Collectively, the GGE-GTCS-related cortical vulnerabilities were associated with chromosomes 4, 5, 11 and 16 and were dispersed bottom-up at the cellular, pathway and disease levels, which contributed to epileptogenesis, suggesting diverse neurobiologically relevant enrichments in GGE-GTCS., Conclusions: By bridging the gaps between transcriptional signatures and in vivo neuroimaging, we highlighted the importance of using MSN abnormalities of the human brain in GGE-GTCS patients to investigate disease-relevant genes and biological processes., (© 2022 British Neuropathological Society.)

Objectives: To explore the differences in the cortical morphometric similarity network (MSN) between COVID-19 survivors and healthy controls, and the correlation between these differences and behavioralfeatures and transcriptional signatures., Materials & Methods: 39 COVID-19 survivors and 39 age-, sex- and education years-matched healthy controls (HCs) were included. All participants underwent MRI and behavioral assessments (PCL-17, GAD-7, PHQ-9). MSN analysis was used to compute COVID-19 survivors vs. HCs differences across brain regions. Correlation analysis was used to determine the associations between regional MSN differences and behavioral assessments, and determine the spatial similarities between regional MSN differences and risk genes transcriptional activity., Results: COVID-19 survivors exhibited decreased regional MSN in insula, precuneus, transverse temporal, entorhinal, para-hippocampal, rostral middle frontal and supramarginal cortices, and increased regional MSN in pars triangularis, lateral orbitofrontal, superior frontal, superior parietal, postcentral, and inferior temporal cortices. Regional MSN value of lateral orbitofrontal cortex was positively associated with GAD-7 and PHQ-9 scores, and rostral middle frontal was negatively related to PHQ-9 scores. The analysis of spatial similarities showed that seven risk genes (MFGE8, MOB2, NUP62, PMPCA, SDSL, TMEM178B, and ZBTB11) were related to regional MSN values., Conclusion: The MSN differences were associated with behavioral and transcriptional signatures, early psychological counseling or intervention may be required to COVID-19 survivors. Our study provided a new insight into understanding the altered coordination of structure in COVID-19 and may offer a new endophenotype to further investigate the brain substrate., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)