Alteration of the fecal microbiota in Chinese children with autism spectrum disorder / Xinyan XIE in Autism Research, 15-6 (June 2022)  

Public ISBD [article]  inAutism Research > 15-6 (June 2022) . - p.996-1007 Titre : Alteration of the fecal microbiota in Chinese children with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Xinyan XIE, Auteur ; Li LI, Auteur ; Xiaoqian WU, Auteur ; Fang HOU, Auteur ; Yanlin CHEN, Auteur ; Liuwei SHI, Auteur ; Qi LIU, Auteur ; Kaiheng ZHU, Auteur ; Qi JIANG, Auteur ; Yanan FENG, Auteur ; Pei XIAO, Auteur ; Jiajia ZHANG, Auteur ; Jianhua GONG, Auteur ; Ranran SONG, Auteur Article en page(s) : p.996-1007 Langues : Anglais (eng) Mots-clés : Autism Spectrum Disorder/complications  Bacteria/genetics  Case-Control Studies  Child  Dysbiosis/complications  Feces/microbiology  Humans  Microbiota  Phylogeny  Chinese Han population  autism spectrum disorder  children  gut microbiota Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is associated with altered gut microbiota. However, there has been little consensus on the altered bacterial species and studies have had small sample sizes. We aimed to identify the taxonomic composition and evaluate the changes in the fecal microbiota in Chinese children with ASD by using a relatively large sample size. We conducted a case-control study of 101 children with ASD and 103 healthy controls in China. Demographic information and fecal samples were collected, and the V3-V4 hypervariable regions of the bacterial 16S ribosomal RNA (rRNA) gene were sequenced. The alpha and beta diversities between the two groups were significantly different. After correcting for multiple comparisons, at the phylum level the relative abundances of Actinobacteria and Proteobacteria in the case group were significantly higher than those in the control group. The relative abundance of the Escherichia-Shigella genus in the case group was significantly higher than that of the control group, and the relative abundance of Blautia and unclassified_f__Lachnospiraceae in the control group were higher than that of the case group. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States analysis showed that children with ASD may have disturbed functional pathways, such as amino acid metabolism, cofactor and vitamin metabolism, and the AMP-activated protein kinase signaling pathway. This study revealed the characteristics of the intestinal flora of Chinese children with ASD and provided further evidence of gut microbial dysbiosis in ASD. LAY SUMMARY: This study characterized the gut microbiota composition of 101 children with ASD and 103 healthy controls in China. The altered gut microbiota may contribute significantly to the risk of ASD, including significant increases in the relative abundances of Actinobacteria, Proteobacteria and Escherichia-Shigella and significant decrease of Blautia and unclassified_f__Lachnospiraceae. This study provided further evidence of gut microbial dysbiosis in ASD. En ligne : http://dx.doi.org/10.1002/aur.2718 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=476 [article] Alteration of the fecal microbiota in Chinese children with autism spectrum disorder [Texte imprimé et/ou numérique] / Xinyan XIE, Auteur ; Li LI, Auteur ; Xiaoqian WU, Auteur ; Fang HOU, Auteur ; Yanlin CHEN, Auteur ; Liuwei SHI, Auteur ; Qi LIU, Auteur ; Kaiheng ZHU, Auteur ; Qi JIANG, Auteur ; Yanan FENG, Auteur ; Pei XIAO, Auteur ; Jiajia ZHANG, Auteur ; Jianhua GONG, Auteur ; Ranran SONG, Auteur . - p.996-1007. Langues : Anglais (eng) in Autism Research > 15-6 (June 2022) . - p.996-1007 Mots-clés : Autism Spectrum Disorder/complications  Bacteria/genetics  Case-Control Studies  Child  Dysbiosis/complications  Feces/microbiology  Humans  Microbiota  Phylogeny  Chinese Han population  autism spectrum disorder  children  gut microbiota Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is associated with altered gut microbiota. However, there has been little consensus on the altered bacterial species and studies have had small sample sizes. We aimed to identify the taxonomic composition and evaluate the changes in the fecal microbiota in Chinese children with ASD by using a relatively large sample size. We conducted a case-control study of 101 children with ASD and 103 healthy controls in China. Demographic information and fecal samples were collected, and the V3-V4 hypervariable regions of the bacterial 16S ribosomal RNA (rRNA) gene were sequenced. The alpha and beta diversities between the two groups were significantly different. After correcting for multiple comparisons, at the phylum level the relative abundances of Actinobacteria and Proteobacteria in the case group were significantly higher than those in the control group. The relative abundance of the Escherichia-Shigella genus in the case group was significantly higher than that of the control group, and the relative abundance of Blautia and unclassified_f__Lachnospiraceae in the control group were higher than that of the case group. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States analysis showed that children with ASD may have disturbed functional pathways, such as amino acid metabolism, cofactor and vitamin metabolism, and the AMP-activated protein kinase signaling pathway. This study revealed the characteristics of the intestinal flora of Chinese children with ASD and provided further evidence of gut microbial dysbiosis in ASD. LAY SUMMARY: This study characterized the gut microbiota composition of 101 children with ASD and 103 healthy controls in China. The altered gut microbiota may contribute significantly to the risk of ASD, including significant increases in the relative abundances of Actinobacteria, Proteobacteria and Escherichia-Shigella and significant decrease of Blautia and unclassified_f__Lachnospiraceae. This study provided further evidence of gut microbial dysbiosis in ASD. En ligne : http://dx.doi.org/10.1002/aur.2718 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=476

Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder / Peng QING in Molecular Autism, 15 (2024)  

Public ISBD [article]  inMolecular Autism > 15 (2024) . - 43p. Titre : Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Peng QING, Auteur ; Xiaodong ZHANG, Auteur ; Qi LIU, Auteur ; Linghong HUANG, Auteur ; Dan XU, Auteur ; Jiao LE, Auteur ; Keith M. KENDRICK, Auteur ; Hua LAI, Auteur ; Weihua ZHAO, Auteur Article en page(s) : 43p. Langues : Anglais (eng) Mots-clés : Humans  White Matter/diagnostic imaging/pathology/physiopathology  Autism Spectrum Disorder/physiopathology/diagnostic imaging  Male  Female  Diffusion Tensor Imaging  Adolescent  Child  Adult  Young Adult  Structure-Activity Relationship  Magnetic Resonance Imaging  Autism spectrum disorder  Diffusion tensor  Functional connectivity tensor  Structure-function coupling  White matter tracts Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder associated with alterations in structural and functional coupling in gray matter. However, despite the detectability and modulation of brain signals in white matter, the structure-function coupling in white matter in autism remains less explored. METHODS: In this study, we investigated structural-functional coupling in white matter (WM) regions, by integrating diffusion tensor data that contain fiber orientation information from WM tracts, with functional connectivity tensor data that reflect local functional anisotropy information. Using functional and diffusion magnetic resonance images, we analyzed a cohort of 89 ASD and 63 typically developing (TD) individuals from the Autism Brain Imaging Data Exchange II (ABIDE-II). Subsequently, the associations between structural-functional coupling in WM regions and ASD severity symptoms assessed by Autism Diagnostic Observation Schedule-2 were examined via supervised machine learning in an independent test cohort of 29 ASD individuals. Furthermore, we also compared the performance of multi-model features (i.e. structural-functional coupling) with single-model features (i.e. functional or structural models alone). RESULTS: In the discovery cohort (ABIDE-II), individuals with ASD exhibited widespread reductions in structural-functional coupling in WM regions compared to TD individuals, particularly in commissural tracts (e.g. corpus callosum), association tracts (sagittal stratum), and projection tracts (e.g. internal capsule). Notably, supervised machine learning analysis in the independent test cohort revealed a significant correlation between these alterations in structural-functional coupling and ASD severity scores. Furthermore, compared to single-model features, the integration of multi-model features (i.e., structural-functional coupling) performed best in predicting ASD severity scores. CONCLUSION: This work provides novel evidence for atypical structural-functional coupling in ASD in white matter regions, further refining our understanding of the critical role of WM networks in the pathophysiology of ASD. En ligne : https://dx.doi.org/10.1186/s13229-024-00620-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538 [article] Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder [Texte imprimé et/ou numérique] / Peng QING, Auteur ; Xiaodong ZHANG, Auteur ; Qi LIU, Auteur ; Linghong HUANG, Auteur ; Dan XU, Auteur ; Jiao LE, Auteur ; Keith M. KENDRICK, Auteur ; Hua LAI, Auteur ; Weihua ZHAO, Auteur . - 43p. Langues : Anglais (eng) in Molecular Autism > 15 (2024) . - 43p. Mots-clés : Humans  White Matter/diagnostic imaging/pathology/physiopathology  Autism Spectrum Disorder/physiopathology/diagnostic imaging  Male  Female  Diffusion Tensor Imaging  Adolescent  Child  Adult  Young Adult  Structure-Activity Relationship  Magnetic Resonance Imaging  Autism spectrum disorder  Diffusion tensor  Functional connectivity tensor  Structure-function coupling  White matter tracts Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder associated with alterations in structural and functional coupling in gray matter. However, despite the detectability and modulation of brain signals in white matter, the structure-function coupling in white matter in autism remains less explored. METHODS: In this study, we investigated structural-functional coupling in white matter (WM) regions, by integrating diffusion tensor data that contain fiber orientation information from WM tracts, with functional connectivity tensor data that reflect local functional anisotropy information. Using functional and diffusion magnetic resonance images, we analyzed a cohort of 89 ASD and 63 typically developing (TD) individuals from the Autism Brain Imaging Data Exchange II (ABIDE-II). Subsequently, the associations between structural-functional coupling in WM regions and ASD severity symptoms assessed by Autism Diagnostic Observation Schedule-2 were examined via supervised machine learning in an independent test cohort of 29 ASD individuals. Furthermore, we also compared the performance of multi-model features (i.e. structural-functional coupling) with single-model features (i.e. functional or structural models alone). RESULTS: In the discovery cohort (ABIDE-II), individuals with ASD exhibited widespread reductions in structural-functional coupling in WM regions compared to TD individuals, particularly in commissural tracts (e.g. corpus callosum), association tracts (sagittal stratum), and projection tracts (e.g. internal capsule). Notably, supervised machine learning analysis in the independent test cohort revealed a significant correlation between these alterations in structural-functional coupling and ASD severity scores. Furthermore, compared to single-model features, the integration of multi-model features (i.e., structural-functional coupling) performed best in predicting ASD severity scores. CONCLUSION: This work provides novel evidence for atypical structural-functional coupling in ASD in white matter regions, further refining our understanding of the critical role of WM networks in the pathophysiology of ASD. En ligne : https://dx.doi.org/10.1186/s13229-024-00620-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538

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