Objective:This study aims to investigate sex-specific abnormalities?? in gray matter volume (GMV) in Children with autism spectrum disorder (ASD) and their associations with gene expression.Methods:T 1-weighted brain MRI data were collected at the MRI Center of the University of Electronic Science and Technology of China between 2022 and 2023 from 100 children with ASD and 90 typically developing (TD) children. Voxel-based morphometry (VBM) was used to explore GMV differences between ASD boys and TD boys, and between ASD girls and TD girls. Partial least squares regression (PLSR) was performed based on the Allen Human Brain Atlas to identify genes associated with GMV alterations, followed by enrichment analyses. Cell-type-specific expression analyses were used to examine associations across developmental stages and brain structures. Protein-protein interaction (PPI) networks were constructed to identify hub proteins. Results:Compared to TD boys, ASD boys showed increased GMV in the right superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, temporal pole, parahippocampal gyrus, fusiform gyrus, cuneus, and precuneus, as well as in the bilateral orbital part of the superior frontal gyrus and the gyrus rectus. Decreased GMV was observed in the cerebellar vermis and bilateral cerebellar hemispheres. A total of 635 genes were associated with these GMV alterations, enriched in pathways related to DNA-templated transcription, RNA metabolism and biogenesis, and ion binding. Developmental analysis indicated strong associations with the cerebellum during early, middle-to-late childhood, and adolescence, and with the cerebral cortex in early adulthood. Protein-protein interaction (PPI) network analysis highlighted NOB1, GNL3L, ESF1, TFB2M, and WDR75 as specific hub proteins. Compared to TD girls, ASD girls exhibited increased GMV in the right middle and inferior temporal gyri, temporal pole, and fusiform gyrus, and decreased GMV in the cerebellar vermis and bilateral cerebellar hemispheres. A total of 765 genes were associated, enriched in pathways related to ion channel activity, signal transduction, and regulation of membrane potential. These genes showed strong associations with the amygdala during mid-to-late fetal development, middle-to-late childhood, adolescence, and early adulthood; with the cerebellum during late infancy, early childhood, and early adulthood; with the cerebral cortex during the mid-to-late fetal development, early neonatal period, and adolescence; with the hippocampus during middle-to-late childhood and adolescence; with the striatum during adolescence and early adulthood; and with the thalamus during early-to-mid fetal development, early neonatal period, and early adulthood. PPI network analysis identified ANK3, ANK1, SCN4B, NFKB1, and PXN as specific hub proteins. Conclusion:Both ASD boys and ASD girls exhibit GMV abnormalities compared with TD controls. The specific genes associated with GMV alterations are enriched in distinct biological pathways in boys and girls. Cell-type-specific expression analyses further revealed sex-dependent differences in developmental timing and brain structural correlations, and distinct PPI networks were constructed for each group.

Autism spectrum disorder(ASD),characterized by unknown etiology and high heterogeneity,ne-cessitates precise diagnostic and intervention strategies.Neuroimaging techniques have shown great promise in un-covering the neural mechanisms of ASD,providing a foundation for aided diagnosis and transcranial magnetic stim-ulation(TMS)interventions.This review highlights that integrating multimodal neuroimaging and developing indi-vidualized indices with developmental specificity can significantly improve the accuracy of ASD diagnosis and clas-sification.Furthermore,TMS interventions guided by functional connectivity derived from functional magnetic reso-nance imaging(fMRI)offer a personalized approach to ASD treatment.

Autism spectrum disorder(ASD),characterized by unknown etiology and high heterogeneity,ne-cessitates precise diagnostic and intervention strategies.Neuroimaging techniques have shown great promise in un-covering the neural mechanisms of ASD,providing a foundation for aided diagnosis and transcranial magnetic stim-ulation(TMS)interventions.This review highlights that integrating multimodal neuroimaging and developing indi-vidualized indices with developmental specificity can significantly improve the accuracy of ASD diagnosis and clas-sification.Furthermore,TMS interventions guided by functional connectivity derived from functional magnetic reso-nance imaging(fMRI)offer a personalized approach to ASD treatment.

Objective:This study aims to investigate sex-specific abnormalities?? in gray matter volume (GMV) in Children with autism spectrum disorder (ASD) and their associations with gene expression.Methods:T 1-weighted brain MRI data were collected at the MRI Center of the University of Electronic Science and Technology of China between 2022 and 2023 from 100 children with ASD and 90 typically developing (TD) children. Voxel-based morphometry (VBM) was used to explore GMV differences between ASD boys and TD boys, and between ASD girls and TD girls. Partial least squares regression (PLSR) was performed based on the Allen Human Brain Atlas to identify genes associated with GMV alterations, followed by enrichment analyses. Cell-type-specific expression analyses were used to examine associations across developmental stages and brain structures. Protein-protein interaction (PPI) networks were constructed to identify hub proteins. Results:Compared to TD boys, ASD boys showed increased GMV in the right superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, temporal pole, parahippocampal gyrus, fusiform gyrus, cuneus, and precuneus, as well as in the bilateral orbital part of the superior frontal gyrus and the gyrus rectus. Decreased GMV was observed in the cerebellar vermis and bilateral cerebellar hemispheres. A total of 635 genes were associated with these GMV alterations, enriched in pathways related to DNA-templated transcription, RNA metabolism and biogenesis, and ion binding. Developmental analysis indicated strong associations with the cerebellum during early, middle-to-late childhood, and adolescence, and with the cerebral cortex in early adulthood. Protein-protein interaction (PPI) network analysis highlighted NOB1, GNL3L, ESF1, TFB2M, and WDR75 as specific hub proteins. Compared to TD girls, ASD girls exhibited increased GMV in the right middle and inferior temporal gyri, temporal pole, and fusiform gyrus, and decreased GMV in the cerebellar vermis and bilateral cerebellar hemispheres. A total of 765 genes were associated, enriched in pathways related to ion channel activity, signal transduction, and regulation of membrane potential. These genes showed strong associations with the amygdala during mid-to-late fetal development, middle-to-late childhood, adolescence, and early adulthood; with the cerebellum during late infancy, early childhood, and early adulthood; with the cerebral cortex during the mid-to-late fetal development, early neonatal period, and adolescence; with the hippocampus during middle-to-late childhood and adolescence; with the striatum during adolescence and early adulthood; and with the thalamus during early-to-mid fetal development, early neonatal period, and early adulthood. PPI network analysis identified ANK3, ANK1, SCN4B, NFKB1, and PXN as specific hub proteins. Conclusion:Both ASD boys and ASD girls exhibit GMV abnormalities compared with TD controls. The specific genes associated with GMV alterations are enriched in distinct biological pathways in boys and girls. Cell-type-specific expression analyses further revealed sex-dependent differences in developmental timing and brain structural correlations, and distinct PPI networks were constructed for each group.

Objective:This study aims to explore the abnormal instantaneous coactivation pattern of the key nodes of default mode network (DMN) and its relationship with social deficits in participants with autism spectrum disorder (ASD).Methods:This study included participants (ASD: n=354, healthy control (HC): n=446) from the Autism Brain Imaging Data Exchange (ABIDE), which is a multi-center and large-sample resting-state functional magnetic resonance imaging (rs-fMRI) database. Coactivation pattern (CAP) analysis was used to explore the coactivation pattern characteristics of medial prefrontal cortex (mPFC), the key node of DMN, and its abnormal interaction with other key nodes of DMN as well as task-positive network. Network dissociation index (NDI) was used to capture the extent of functional dissociation within and between networks and predict the clinical symptoms of ASD based on multi-variable support vector regression. Results:When mPFC was activated, precuneus, another key node of DMN, showed lower activation in participants with ASD than those in the HC group ( t=-4.21, P<0.01). Instead, dorsal anterior cingulate cortex (dACC) and orbital fronto-insula junction, key nodes of the salience network (SN), showed higher activation in participants with ASD than those in the HC group ( t=2.93, 2.61, all P<0.05). Additionally, compared with HC, ASD showed significantly higher NDI within DMN ( t=3.63, P<0.01) and significantly lower NDI between DMN and SN (dACC and orbital fronto-insula junction) ( t=-2.97, -3.31, all P<0.01). Additionally, using multi-variable support vector regression model, altered NDI could well predict social, speech communication deficits and disease severity of ASD ( r=0.191,0.216,0.186, all P<0.01). Conclusion:The CAP of mPFC in ASD in resting state was abnormal, which reflected the decreased functional integration within DMN and the decreased functional segregation between DMN and task-positive network. Besides, this abnormal network function pattern was closely related to clinical symptoms of ASD.

Objective:This study aims to explore the abnormal instantaneous coactivation pattern of the key nodes of default mode network (DMN) and its relationship with social deficits in participants with autism spectrum disorder (ASD).Methods:This study included participants (ASD: n=354, healthy control (HC): n=446) from the Autism Brain Imaging Data Exchange (ABIDE), which is a multi-center and large-sample resting-state functional magnetic resonance imaging (rs-fMRI) database. Coactivation pattern (CAP) analysis was used to explore the coactivation pattern characteristics of medial prefrontal cortex (mPFC), the key node of DMN, and its abnormal interaction with other key nodes of DMN as well as task-positive network. Network dissociation index (NDI) was used to capture the extent of functional dissociation within and between networks and predict the clinical symptoms of ASD based on multi-variable support vector regression. Results:When mPFC was activated, precuneus, another key node of DMN, showed lower activation in participants with ASD than those in the HC group ( t=-4.21, P<0.01). Instead, dorsal anterior cingulate cortex (dACC) and orbital fronto-insula junction, key nodes of the salience network (SN), showed higher activation in participants with ASD than those in the HC group ( t=2.93, 2.61, all P<0.05). Additionally, compared with HC, ASD showed significantly higher NDI within DMN ( t=3.63, P<0.01) and significantly lower NDI between DMN and SN (dACC and orbital fronto-insula junction) ( t=-2.97, -3.31, all P<0.01). Additionally, using multi-variable support vector regression model, altered NDI could well predict social, speech communication deficits and disease severity of ASD ( r=0.191,0.216,0.186, all P<0.01). Conclusion:The CAP of mPFC in ASD in resting state was abnormal, which reflected the decreased functional integration within DMN and the decreased functional segregation between DMN and task-positive network. Besides, this abnormal network function pattern was closely related to clinical symptoms of ASD.

Objective:To investigate the associations of brain white matter integrity deficits, and to explore the association of fractional anisotropy (FA) abnormality with clinical symptoms and cognitive impairments, as well as the prediction effect of the FA alterations on symptoms and cognitive function outcomes in the acute stage of schizophrenia from the whole brain level based on magnetic resonance diffusion tensor imaging (DTI).Methods:From November 2019 to December 2020, thirty-eight patients with first-episode schizophrenia and 38 healthy controls were recruited in this study. Wisconsin card classification test (WCST), digit span test (DST forward/backward), verbal fluency test, Stroop (A/B/C), trail making test (TMT-A/B), as well as positive and negative syndrome scale (PANSS) were utilized to evaluate patients' cognitive function and clinical symptoms both before and after 8 weeks of risperidone monotherapy. T1-weighted images and DTI data of all the subjects were collected . FSL and SPM8 were used to preprocess MRI data and compare the between-group differences of FA. Support vector machine (SVM) analysis was used to evaluate the accuracy of abnormal FA values in differentiating schizophrenic patients from healthy controls. Finally, stepwise multiple regression analysis or generalized linear models were used to explore the associations between white matter integrity and symptoms or cognition.Results:Before treatment, patients' FA values of right medial temporal lobe (mTL), cuneus, anterior cingulate gyrus (ACG) and inferior parietal lobe (IPL) were significantly lower than those in healthy controls ( P<0.01, GRF corrected), and patients' FA values of bilateral middle cingulate gyrus (mCG) were significantly higher than those in the control group ( P<0.01, GRF corrected). SVM analysis showed that four combinations could distinguish the patients from the control with the most accurate rate of 89.47%. Patients' baseline decreased FA values in the right IPL were positively associated with their increased total response time in WCST ( β=0.489, P=0.003, FDR corrected), correct response time in WCST ( β=0.450, P=0.008, FDR corrected), error response time in WCST ( β=0.435, P=0.008, FDR corrected), TMT-B ( β=0.296, P=0.042, FDR corrected), Stroop-C ( β=0.345, P=0.035, FDR corrected), and PANSS-P ( β=0.321, P=0.042, FDR corrected). Reduced FA values in the right mTL in patient group were significantly negatively related to the total time spent on the TMT-A ( β=-0.425, P=0.009, FDR corrected) and TMT-B ( β=-0.325, P=0.026 with FDR correction). Increased FA values in right mCG in patient group demonstrated positive associations with total response time in the WCST ( β=0.585, P=0.002, FDR corrected), correct response time in WCST ( β=0.524, P=0.003, FDR corrected), error response time in WCST ( β=0.536, P=0.003, FDR corrected) and total time consuming in TMT-B ( β=0.484, P=0.004, FDR corrected), as well as negative associations with DST-forward ( β=-0.319, P=0.042, FDR corrected). After treatment, patients' percentage changes in total response time of WCST ( β=0.715, P<0.001, FDR corrected), correct response time of WCST ( β=0.752, P<0.001, FDR corrected), as well as total time-consuming of TMT-A ( β=1.333, P=0.001, FDR corrected) showed positive correlations with baseline increased FA values in the left mCG. Percentage alteration of Stroop-B was negatively correlated with baseline FA values in the right cuneus ( β=-0.745, P=0.015, FDR corrected). Conclusions:The combination of abnormal FA values in multiple brain regions may be potential biomarkers to distinguish schizophrenic patients from healthy volunteers. There was regional dependence in the associations of the impairment of white matter integrity with the cognitive impairment, the severity of psychopathological symptoms as well as the prognosis of patients in the acute stage.