Causal Network Analysis Reveals Key Brain Regions Associated With Severity in Children With Autism Spectrum Disorder / Xiaofen SUN in Autism Research, 18-9 (September 2025)  

Public ISBD [article]  inAutism Research > 18-9 (September 2025) . - p.1746-1763 Titre : Causal Network Analysis Reveals Key Brain Regions Associated With Severity in Children With Autism Spectrum Disorder Type de document : texte imprimé Auteurs : Xiaofen SUN, Auteur ; Haibo WANG, Auteur ; Jingbo DENG, Auteur ; Shitong CHENG, Auteur ; Xiaocheng WANG, Auteur ; Chenghui FU, Auteur ; Ling LI, Auteur ; Yuefu ZHAN, Auteur ; Jianqiang CHEN, Auteur Article en page(s) : p.1746-1763 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  brain structure  gGranger causality analysis  gray matter density  parahippocampal gyrus Index. décimale : PER Périodiques Résumé : ABSTRACT This study aims to investigate the relationship between gray matter (GM) changes and severity in children with Autism Spectrum Disorder (ASD). We examined 113 ASD children aged 2 8 years (17 mild cases, 56 moderate cases, and 40 severe cases), as well as 110 age and sex-matched healthy controls (HC). Voxel-based morphometry (VBM) was used to compare GM density (GMD) changes between ASD and HC groups. Additionally, structural covariance network analysis quantified the cross-regional synchronous changes in GM among ASD children, and causal analysis described the pattern of changes in the GM network related to symptom severity in ASD children. The results indicated that ASD children exhibiting mild symptoms have an enlarged parahippocampal gyrus, and as the severity of ASD increases, the range of GMD changes expands (p=0.05, FDR correction). Granger causality (GC) analysis revealed that the parahippocampal gyrus may function as a central hub within ASD-related directional networks, exerting causal effects on other brain regions (p=0.05). These findings were validated by external datasets. Our results provide preliminary insights into the role of the parahippocampal gyrus in ASD and promote the application of dimensional models. En ligne : https://doi.org/10.1002/aur.70098 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=568 [article] Causal Network Analysis Reveals Key Brain Regions Associated With Severity in Children With Autism Spectrum Disorder [texte imprimé] / Xiaofen SUN, Auteur ; Haibo WANG, Auteur ; Jingbo DENG, Auteur ; Shitong CHENG, Auteur ; Xiaocheng WANG, Auteur ; Chenghui FU, Auteur ; Ling LI, Auteur ; Yuefu ZHAN, Auteur ; Jianqiang CHEN, Auteur . - p.1746-1763. Langues : Anglais (eng) in Autism Research > 18-9 (September 2025) . - p.1746-1763 Mots-clés : autism spectrum disorder  brain structure  gGranger causality analysis  gray matter density  parahippocampal gyrus Index. décimale : PER Périodiques Résumé : ABSTRACT This study aims to investigate the relationship between gray matter (GM) changes and severity in children with Autism Spectrum Disorder (ASD). We examined 113 ASD children aged 2 8 years (17 mild cases, 56 moderate cases, and 40 severe cases), as well as 110 age and sex-matched healthy controls (HC). Voxel-based morphometry (VBM) was used to compare GM density (GMD) changes between ASD and HC groups. Additionally, structural covariance network analysis quantified the cross-regional synchronous changes in GM among ASD children, and causal analysis described the pattern of changes in the GM network related to symptom severity in ASD children. The results indicated that ASD children exhibiting mild symptoms have an enlarged parahippocampal gyrus, and as the severity of ASD increases, the range of GMD changes expands (p=0.05, FDR correction). Granger causality (GC) analysis revealed that the parahippocampal gyrus may function as a central hub within ASD-related directional networks, exerting causal effects on other brain regions (p=0.05). These findings were validated by external datasets. Our results provide preliminary insights into the role of the parahippocampal gyrus in ASD and promote the application of dimensional models. En ligne : https://doi.org/10.1002/aur.70098 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=568

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