Decreased functional concordance in male children with autism spectrum disorder / Sha WANG ; Zaifa XUE ; Jing LIU ; Xiaoxia NIU ; Le GAO ; Xiaonan GUO in Autism Research, 16-12 (December 2023)  

Public ISBD [article]  inAutism Research > 16-12 (December 2023) . - p.2263-2274 Titre : Decreased functional concordance in male children with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Sha WANG, Auteur ; Zaifa XUE, Auteur ; Jing LIU, Auteur ; Xiaoxia NIU, Auteur ; Le GAO, Auteur ; Xiaonan GUO, Auteur Article en page(s) : p.2263-2274 Index. décimale : PER Périodiques Résumé : Abstract Autism spectrum disorder (ASD) is an early-onset neurodevelopmental condition with altered function of the brain. At present, a variety of functional metrics from neuroimaging techniques have been used to explore ASD neurological mechanisms. However, the concordance of these functional metrics in ASD is still unclear. This study used resting-state functional magnetic resonance imaging data, which were obtained from the open-access Autism Brain Imaging Data Exchange database, including 105 children with ASD and 102 demographically matched typically developing (TD) children. Both voxel-wise and volume-wise functional concordance were calculated by combining the dynamic amplitude of low-frequency fluctuations, dynamic regional homogeneity, and dynamic global signal correlation. Furthermore, a two-sample t-test was performed to compare the functional concordance between ASD and TD groups. Finally, the relationship between voxel-wise functional concordance and Autism Diagnostic Observation Schedule subscores was analyzed using the multivariate support vector regression in the ASD group. Compared with the TD group, we found that ASD showed decreased voxel-wise functional concordance in the left superior temporal pole (STGp), right amygdala, and left opercular part of the inferior frontal gyrus (IFGoper). Moreover, decreased functional concordance was associated with restricted and repetitive behaviors in ASD. Our results found altered brain function in the left STGp, right amygdala, and left IFGoper in ASD by functional concordance, indicating that functional concordance may provide new insights into the neurological mechanisms of ASD. En ligne : https://doi.org/10.1002/aur.3035 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518 [article] Decreased functional concordance in male children with autism spectrum disorder [Texte imprimé et/ou numérique] / Sha WANG, Auteur ; Zaifa XUE, Auteur ; Jing LIU, Auteur ; Xiaoxia NIU, Auteur ; Le GAO, Auteur ; Xiaonan GUO, Auteur . - p.2263-2274. in Autism Research > 16-12 (December 2023) . - p.2263-2274 Index. décimale : PER Périodiques Résumé : Abstract Autism spectrum disorder (ASD) is an early-onset neurodevelopmental condition with altered function of the brain. At present, a variety of functional metrics from neuroimaging techniques have been used to explore ASD neurological mechanisms. However, the concordance of these functional metrics in ASD is still unclear. This study used resting-state functional magnetic resonance imaging data, which were obtained from the open-access Autism Brain Imaging Data Exchange database, including 105 children with ASD and 102 demographically matched typically developing (TD) children. Both voxel-wise and volume-wise functional concordance were calculated by combining the dynamic amplitude of low-frequency fluctuations, dynamic regional homogeneity, and dynamic global signal correlation. Furthermore, a two-sample t-test was performed to compare the functional concordance between ASD and TD groups. Finally, the relationship between voxel-wise functional concordance and Autism Diagnostic Observation Schedule subscores was analyzed using the multivariate support vector regression in the ASD group. Compared with the TD group, we found that ASD showed decreased voxel-wise functional concordance in the left superior temporal pole (STGp), right amygdala, and left opercular part of the inferior frontal gyrus (IFGoper). Moreover, decreased functional concordance was associated with restricted and repetitive behaviors in ASD. Our results found altered brain function in the left STGp, right amygdala, and left IFGoper in ASD by functional concordance, indicating that functional concordance may provide new insights into the neurological mechanisms of ASD. En ligne : https://doi.org/10.1002/aur.3035 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518

Inter-individual heterogeneity of functional brain networks in children with autism spectrum disorder / Xiaonan GUO in Molecular Autism, 13 (2022)  

Public ISBD [article]  inMolecular Autism > 13 (2022) . - 52 p. Titre : Inter-individual heterogeneity of functional brain networks in children with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Xiaonan GUO, Auteur ; Guangjin ZHAI, Auteur ; Junfeng LIU, Auteur ; Yabo CAO, Auteur ; Xia ZHANG, Auteur ; Dong CUI, Auteur ; Le GAO, Auteur Article en page(s) : 52 p. Langues : Anglais (eng) Mots-clés : Humans  Male  Child  Autism Spectrum Disorder/diagnostic imaging  Brain Mapping/methods  Magnetic Resonance Imaging/methods  Brain/diagnostic imaging  Autistic Disorder  Neural Pathways/diagnostic imaging  Autism spectrum disorder  Functional connectivity  Functional magnetic resonance imaging  Subtype  k-means clustering Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with considerable clinical heterogeneity. This study aimed to explore the heterogeneity of ASD based on inter-individual heterogeneity of functional brain networks. METHODS: Resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database were used in this study for 105 children with ASD and 102 demographically matched typical controls (TC) children. Functional connectivity (FC) networks were first obtained for ASD and TC groups, and inter-individual deviation of functional connectivity (IDFC) from the TC group was then calculated for each individual with ASD. A k-means clustering algorithm was used to obtain ASD subtypes based on IDFC patterns. The FC patterns were further compared between ASD subtypes and the TC group from the brain region, network, and whole-brain levels. The relationship between IDFC and the severity of clinical symptoms of ASD for ASD subtypes was also analyzed using a support vector regression model. RESULTS: Two ASD subtypes were identified based on the IDFC patterns. Compared with the TC group, the ASD subtype 1 group exhibited a hypoconnectivity pattern and the ASD subtype 2 group exhibited a hyperconnectivity pattern. IDFC for ASD subtype 1 and subtype 2 was found to predict the severity of social communication impairments and the severity of restricted and repetitive behaviors in ASD, respectively. LIMITATIONS: Only male children were selected for this study, which limits the ability to study the effects of gender and development on ASD heterogeneity. CONCLUSIONS: These results suggest the existence of subtypes with different FC patterns in ASD and provide insight into the complex pathophysiological mechanism of clinical manifestations of ASD. En ligne : http://dx.doi.org/10.1186/s13229-022-00535-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=491 [article] Inter-individual heterogeneity of functional brain networks in children with autism spectrum disorder [Texte imprimé et/ou numérique] / Xiaonan GUO, Auteur ; Guangjin ZHAI, Auteur ; Junfeng LIU, Auteur ; Yabo CAO, Auteur ; Xia ZHANG, Auteur ; Dong CUI, Auteur ; Le GAO, Auteur . - 52 p. Langues : Anglais (eng) in Molecular Autism > 13 (2022) . - 52 p. Mots-clés : Humans  Male  Child  Autism Spectrum Disorder/diagnostic imaging  Brain Mapping/methods  Magnetic Resonance Imaging/methods  Brain/diagnostic imaging  Autistic Disorder  Neural Pathways/diagnostic imaging  Autism spectrum disorder  Functional connectivity  Functional magnetic resonance imaging  Subtype  k-means clustering Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with considerable clinical heterogeneity. This study aimed to explore the heterogeneity of ASD based on inter-individual heterogeneity of functional brain networks. METHODS: Resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database were used in this study for 105 children with ASD and 102 demographically matched typical controls (TC) children. Functional connectivity (FC) networks were first obtained for ASD and TC groups, and inter-individual deviation of functional connectivity (IDFC) from the TC group was then calculated for each individual with ASD. A k-means clustering algorithm was used to obtain ASD subtypes based on IDFC patterns. The FC patterns were further compared between ASD subtypes and the TC group from the brain region, network, and whole-brain levels. The relationship between IDFC and the severity of clinical symptoms of ASD for ASD subtypes was also analyzed using a support vector regression model. RESULTS: Two ASD subtypes were identified based on the IDFC patterns. Compared with the TC group, the ASD subtype 1 group exhibited a hypoconnectivity pattern and the ASD subtype 2 group exhibited a hyperconnectivity pattern. IDFC for ASD subtype 1 and subtype 2 was found to predict the severity of social communication impairments and the severity of restricted and repetitive behaviors in ASD, respectively. LIMITATIONS: Only male children were selected for this study, which limits the ability to study the effects of gender and development on ASD heterogeneity. CONCLUSIONS: These results suggest the existence of subtypes with different FC patterns in ASD and provide insight into the complex pathophysiological mechanism of clinical manifestations of ASD. En ligne : http://dx.doi.org/10.1186/s13229-022-00535-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=491

Sex heterogeneity of dynamic brain activity and functional connectivity in autism spectrum disorder / Qi DONG ; Le GAO ; Zaifa XUE ; Xiaoxia NIU ; Rongjuan ZHOU ; Xiaonan GUO in Autism Research, 17-9 (September 2024)  

Public ISBD [article]  inAutism Research > 17-9 (September 2024) . - p.1796-1809 Titre : Sex heterogeneity of dynamic brain activity and functional connectivity in autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Qi DONG, Auteur ; Le GAO, Auteur ; Zaifa XUE, Auteur ; Xiaoxia NIU, Auteur ; Rongjuan ZHOU, Auteur ; Xiaonan GUO, Auteur Article en page(s) : p.1796-1809 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  dynamic amplitude of low-frequency fluctuation  dynamic functional connectivity  resting-state functional magnetic resonance imaging  sex heterogeneity Index. décimale : PER Périodiques Résumé : Abstract Sex heterogeneity has been frequently reported in autism spectrum disorders (ASD) and has been linked to static differences in brain function. However, given the complexity of ASD and diagnosis-by-sex interactions, dynamic characteristics of brain activity and functional connectivity may provide important information for distinguishing ASD phenotypes between females and males. The aim of this study was to explore sex heterogeneity of functional networks in the ASD brain from a dynamic perspective. Resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database were analyzed in 128 ASD subjects (64 males/64 females) and 128 typically developing control (TC) subjects (64 males/64 females). A sliding-window approach was adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dynamic functional connectivity (dFC) to characterize time-varying brain activity and functional connectivity respectively. We then examined the sex-related changes in ASD using two-way analysis of variance. Significant diagnosis-by-sex interaction effects were identified in the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC) and left precuneus in the dALFF analysis. Furthermore, there were significant diagnosis-by-sex interaction effects of dFC variance between the left ACC/mPFC and right ACC, left postcentral gyrus, left precuneus, right middle temporal gyrus and left inferior frontal gyrus, triangular part. These findings reveal the sex heterogeneity in brain activity and functional connectivity in ASD from a dynamic perspective, and provide new evidence for further exploring sex heterogeneity in ASD. En ligne : https://doi.org/10.1002/aur.3227 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=535 [article] Sex heterogeneity of dynamic brain activity and functional connectivity in autism spectrum disorder [Texte imprimé et/ou numérique] / Qi DONG, Auteur ; Le GAO, Auteur ; Zaifa XUE, Auteur ; Xiaoxia NIU, Auteur ; Rongjuan ZHOU, Auteur ; Xiaonan GUO, Auteur . - p.1796-1809. Langues : Anglais (eng) in Autism Research > 17-9 (September 2024) . - p.1796-1809 Mots-clés : autism spectrum disorder  dynamic amplitude of low-frequency fluctuation  dynamic functional connectivity  resting-state functional magnetic resonance imaging  sex heterogeneity Index. décimale : PER Périodiques Résumé : Abstract Sex heterogeneity has been frequently reported in autism spectrum disorders (ASD) and has been linked to static differences in brain function. However, given the complexity of ASD and diagnosis-by-sex interactions, dynamic characteristics of brain activity and functional connectivity may provide important information for distinguishing ASD phenotypes between females and males. The aim of this study was to explore sex heterogeneity of functional networks in the ASD brain from a dynamic perspective. Resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database were analyzed in 128 ASD subjects (64 males/64 females) and 128 typically developing control (TC) subjects (64 males/64 females). A sliding-window approach was adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dynamic functional connectivity (dFC) to characterize time-varying brain activity and functional connectivity respectively. We then examined the sex-related changes in ASD using two-way analysis of variance. Significant diagnosis-by-sex interaction effects were identified in the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC) and left precuneus in the dALFF analysis. Furthermore, there were significant diagnosis-by-sex interaction effects of dFC variance between the left ACC/mPFC and right ACC, left postcentral gyrus, left precuneus, right middle temporal gyrus and left inferior frontal gyrus, triangular part. These findings reveal the sex heterogeneity in brain activity and functional connectivity in ASD from a dynamic perspective, and provide new evidence for further exploring sex heterogeneity in ASD. En ligne : https://doi.org/10.1002/aur.3227 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=535

Shared atypical default mode and salience network functional connectivity between autism and schizophrenia / Heng CHEN in Autism Research, 10-11 (November 2017)  

Public ISBD [article]  inAutism Research > 10-11 (November 2017) . - p.1776-1786 Titre : Shared atypical default mode and salience network functional connectivity between autism and schizophrenia Type de document : Texte imprimé et/ou numérique Auteurs : Heng CHEN, Auteur ; Lucina Q. UDDIN, Auteur ; Xujun DUAN, Auteur ; Junjie ZHENG, Auteur ; Zhiliang LONG, Auteur ; Youxue ZHANG, Auteur ; Xiaonan GUO, Auteur ; Yan ZHANG, Auteur ; Jingping ZHAO, Auteur ; Huafu CHEN, Auteur Article en page(s) : p.1776-1786 Langues : Anglais (eng) Mots-clés : schizophrenia  autism spectrum disorder  functional connectivity  multivariate pattern analysis  default mode network  salience network Index. décimale : PER Périodiques Résumé : Schizophrenia and autism spectrum disorder (ASD) are two prevalent neurodevelopmental disorders sharing some similar genetic basis and clinical features. The extent to which they share common neural substrates remains unclear. Resting-state fMRI data were collected from 35 drug-naïve adolescent participants with first-episode schizophrenia (15.6?±?1.8 years old) and 31 healthy controls (15.4?±?1.6 years old). Data from 22 participants with ASD (13.1?±?3.1 years old) and 21 healthy controls (12.9?±?2.9 years old) were downloaded from the Autism Brain Imaging Data Exchange. Resting-state functional networks were constructed using predefined regions of interest. Multivariate pattern analysis combined with multi-task regression feature selection methods were conducted in two datasets separately. Classification between individuals with disorders and controls was achieved with high accuracy (schizophrenia dataset: accuracy?=?83%; ASD dataset: accuracy?=?80%). Shared atypical brain connections contributing to classification were mostly present in the default mode network (DMN) and salience network (SN). These functional connections were further related to severity of social deficits in ASD (p?=?0.002). Distinct atypical connections were also more related to the DMN and SN, but showed different atypical connectivity patterns between the two disorders. These results suggest some common neural mechanisms contributing to schizophrenia and ASD, and may aid in understanding the pathology of these two neurodevelopmental disorders. Autism Res 2017, 10: 1776–1786. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Lay summary Autism spectrum disorder (ASD) and schizophrenia are two common neurodevelopmental disorders which share several genetic and behavioral features. The present study identified common neural mechanisms contributing to ASD and schizophrenia using resting-state functional MRI data. The results may help to understand the pathology of these two neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1002/aur.1834 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=322 [article] Shared atypical default mode and salience network functional connectivity between autism and schizophrenia [Texte imprimé et/ou numérique] / Heng CHEN, Auteur ; Lucina Q. UDDIN, Auteur ; Xujun DUAN, Auteur ; Junjie ZHENG, Auteur ; Zhiliang LONG, Auteur ; Youxue ZHANG, Auteur ; Xiaonan GUO, Auteur ; Yan ZHANG, Auteur ; Jingping ZHAO, Auteur ; Huafu CHEN, Auteur . - p.1776-1786. Langues : Anglais (eng) in Autism Research > 10-11 (November 2017) . - p.1776-1786 Mots-clés : schizophrenia  autism spectrum disorder  functional connectivity  multivariate pattern analysis  default mode network  salience network Index. décimale : PER Périodiques Résumé : Schizophrenia and autism spectrum disorder (ASD) are two prevalent neurodevelopmental disorders sharing some similar genetic basis and clinical features. The extent to which they share common neural substrates remains unclear. Resting-state fMRI data were collected from 35 drug-naïve adolescent participants with first-episode schizophrenia (15.6?±?1.8 years old) and 31 healthy controls (15.4?±?1.6 years old). Data from 22 participants with ASD (13.1?±?3.1 years old) and 21 healthy controls (12.9?±?2.9 years old) were downloaded from the Autism Brain Imaging Data Exchange. Resting-state functional networks were constructed using predefined regions of interest. Multivariate pattern analysis combined with multi-task regression feature selection methods were conducted in two datasets separately. Classification between individuals with disorders and controls was achieved with high accuracy (schizophrenia dataset: accuracy?=?83%; ASD dataset: accuracy?=?80%). Shared atypical brain connections contributing to classification were mostly present in the default mode network (DMN) and salience network (SN). These functional connections were further related to severity of social deficits in ASD (p?=?0.002). Distinct atypical connections were also more related to the DMN and SN, but showed different atypical connectivity patterns between the two disorders. These results suggest some common neural mechanisms contributing to schizophrenia and ASD, and may aid in understanding the pathology of these two neurodevelopmental disorders. Autism Res 2017, 10: 1776–1786. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Lay summary Autism spectrum disorder (ASD) and schizophrenia are two common neurodevelopmental disorders which share several genetic and behavioral features. The present study identified common neural mechanisms contributing to ASD and schizophrenia using resting-state functional MRI data. The results may help to understand the pathology of these two neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1002/aur.1834 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=322

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