Autism Spectrum Disorder as Early Neurodevelopmental Disorder: Evidence from the Brain Imaging Abnormalities in 2–3 Years Old Toddlers / Zhou XIAO in Journal of Autism and Developmental Disorders, 44-7 (July 2014)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 44-7 (July 2014) . - p.1633-1640 Titre : Autism Spectrum Disorder as Early Neurodevelopmental Disorder: Evidence from the Brain Imaging Abnormalities in 2–3 Years Old Toddlers Type de document : texte imprimé Auteurs : Zhou XIAO, Auteur ; Ting QIU, Auteur ; Xiaoyan KE, Auteur ; Xiang XIAO, Auteur ; Ting XIAO, Auteur ; Fengjing LIANG, Auteur ; Bing ZOU, Auteur ; Haiqing HUANG, Auteur ; Hui FANG, Auteur ; Kangkang CHU, Auteur ; Jiuping ZHANG, Auteur ; Yijun LIU, Auteur Article en page(s) : p.1633-1640 Langues : Anglais (eng) Mots-clés : Autism spectrum disorder  Toddler  Magnetic resonance imaging  Voxel based morphometry  Diffusion tensor imaging Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that occurs within the first 3 years of life, which is marked by social skills and communication deficits along with stereotyped repetitive behavior. Although great efforts have been made to clarify the underlying neuroanatomical abnormalities and brain-behavior relationships in adolescents and adults with ASD, literature is still limited in information about the neurobiology of ASD in the early age of life. Brain images of 50 toddlers with ASD and 28 age, gender, and developmental quotient matched toddlers with developmental delay (DD) (control group) between ages 2 and 3 years were captured using combined magnetic resonance-based structural imaging and diffusion tensor imaging (DTI). Structural magnetic resonance imaging was applied to assess overall gray matter (GM) and white matter (WM) volumes, and regional alterations were assessed by voxel-based morphometry. DTI was used to investigate the white matter tract integrity. Compared with DD, significant increases were observed in ASD, primarily in global GM and WM volumes and in right superior temporal gyrus regional GM and WM volumes. Higher fractional anisotropy value was also observed in the corpus callosum, posterior cingulate cortex, and limbic lobes of ASD. The converging findings of structural and white matter abnormalities in ASD suggest that alterations in neural-anatomy of different brain regions may be involved in behavioral and cognitive deficits associated with ASD, especially in an early age of 2–3 years old toddlers. En ligne : http://dx.doi.org/10.1007/s10803-014-2033-x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=236 [article] Autism Spectrum Disorder as Early Neurodevelopmental Disorder: Evidence from the Brain Imaging Abnormalities in 2–3 Years Old Toddlers [texte imprimé] / Zhou XIAO, Auteur ; Ting QIU, Auteur ; Xiaoyan KE, Auteur ; Xiang XIAO, Auteur ; Ting XIAO, Auteur ; Fengjing LIANG, Auteur ; Bing ZOU, Auteur ; Haiqing HUANG, Auteur ; Hui FANG, Auteur ; Kangkang CHU, Auteur ; Jiuping ZHANG, Auteur ; Yijun LIU, Auteur . - p.1633-1640. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 44-7 (July 2014) . - p.1633-1640 Mots-clés : Autism spectrum disorder  Toddler  Magnetic resonance imaging  Voxel based morphometry  Diffusion tensor imaging Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that occurs within the first 3 years of life, which is marked by social skills and communication deficits along with stereotyped repetitive behavior. Although great efforts have been made to clarify the underlying neuroanatomical abnormalities and brain-behavior relationships in adolescents and adults with ASD, literature is still limited in information about the neurobiology of ASD in the early age of life. Brain images of 50 toddlers with ASD and 28 age, gender, and developmental quotient matched toddlers with developmental delay (DD) (control group) between ages 2 and 3 years were captured using combined magnetic resonance-based structural imaging and diffusion tensor imaging (DTI). Structural magnetic resonance imaging was applied to assess overall gray matter (GM) and white matter (WM) volumes, and regional alterations were assessed by voxel-based morphometry. DTI was used to investigate the white matter tract integrity. Compared with DD, significant increases were observed in ASD, primarily in global GM and WM volumes and in right superior temporal gyrus regional GM and WM volumes. Higher fractional anisotropy value was also observed in the corpus callosum, posterior cingulate cortex, and limbic lobes of ASD. The converging findings of structural and white matter abnormalities in ASD suggest that alterations in neural-anatomy of different brain regions may be involved in behavioral and cognitive deficits associated with ASD, especially in an early age of 2–3 years old toddlers. En ligne : http://dx.doi.org/10.1007/s10803-014-2033-x Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=236

Diagnostic model generated by MRI-derived brain features in toddlers with autism spectrum disorder / Xiang XIAO in Autism Research, 10-4 (April 2017)  

Public ISBD [article]  inAutism Research > 10-4 (April 2017) . - p.620-630 Titre : Diagnostic model generated by MRI-derived brain features in toddlers with autism spectrum disorder Type de document : texte imprimé Auteurs : Xiang XIAO, Auteur ; Hui FANG, Auteur ; Jiansheng WU, Auteur ; ChaoYong XIAO, Auteur ; Ting XIAO, Auteur ; Lu QIAN, Auteur ; Fengjing LIANG, Auteur ; Zhou XIAO, Auteur ; Kangkang CHU, Auteur ; Xiaoyan KE, Auteur Article en page(s) : p.620-630 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  toddler  magnetic resonance imaging  cortical thickness  predictive model Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder mainly showed atypical social interaction, communication, and restricted, repetitive patterns of behavior, interests and activities. Now clinic diagnosis of ASD is mostly based on psychological evaluation, clinical observation and medical history. All these behavioral indexes could not avoid defects such as subjectivity and reporter-dependency. Therefore researchers devoted themselves to seek relatively stable biomarkers of ASD as supplementary diagnostic evidence. The goal of present study is to generate relatively stable predictive model based on anatomical brain features by using machine learning technique. Forty-six ASD children and thirty-nine development delay children aged from 18 to 37 months were evolved in. As a result, the predictive model generated by regional average cortical thickness of regions with top 20 highest importance of random forest classifier showed best diagnostic performance. And random forest was proved to be the optimal approach for neuroimaging data mining in small size set and thickness-based classification outperformed volume-based classification and surface area-based classification in ASD. The brain regions selected by the models might attract attention and the idea of considering biomarkers as a supplementary evidence of ASD diagnosis worth exploring. En ligne : http://dx.doi.org/10.1002/aur.1711 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=307 [article] Diagnostic model generated by MRI-derived brain features in toddlers with autism spectrum disorder [texte imprimé] / Xiang XIAO, Auteur ; Hui FANG, Auteur ; Jiansheng WU, Auteur ; ChaoYong XIAO, Auteur ; Ting XIAO, Auteur ; Lu QIAN, Auteur ; Fengjing LIANG, Auteur ; Zhou XIAO, Auteur ; Kangkang CHU, Auteur ; Xiaoyan KE, Auteur . - p.620-630. Langues : Anglais (eng) in Autism Research > 10-4 (April 2017) . - p.620-630 Mots-clés : autism spectrum disorder  toddler  magnetic resonance imaging  cortical thickness  predictive model Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder mainly showed atypical social interaction, communication, and restricted, repetitive patterns of behavior, interests and activities. Now clinic diagnosis of ASD is mostly based on psychological evaluation, clinical observation and medical history. All these behavioral indexes could not avoid defects such as subjectivity and reporter-dependency. Therefore researchers devoted themselves to seek relatively stable biomarkers of ASD as supplementary diagnostic evidence. The goal of present study is to generate relatively stable predictive model based on anatomical brain features by using machine learning technique. Forty-six ASD children and thirty-nine development delay children aged from 18 to 37 months were evolved in. As a result, the predictive model generated by regional average cortical thickness of regions with top 20 highest importance of random forest classifier showed best diagnostic performance. And random forest was proved to be the optimal approach for neuroimaging data mining in small size set and thickness-based classification outperformed volume-based classification and surface area-based classification in ASD. The brain regions selected by the models might attract attention and the idea of considering biomarkers as a supplementary evidence of ASD diagnosis worth exploring. En ligne : http://dx.doi.org/10.1002/aur.1711 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=307

Trajectories of Autism Symptoms and Overlapping Patterns in a Chinese Cohort From 18 to 36 Months / Feixia ZHANG in Autism Research, 19-5 (May 2026)  

Public ISBD [article]  inAutism Research > 19-5 (May 2026) . - p.e70219 Titre : Trajectories of Autism Symptoms and Overlapping Patterns in a Chinese Cohort From 18 to 36 Months Type de document : texte imprimé Auteurs : Feixia ZHANG, Auteur ; YanTing XU, Auteur ; Linru LIU, Auteur ; Yu XING, Auteur ; Cong YOU, Auteur ; ShaoLi LV, Auteur ; Huishi HUANG, Auteur ; YuanYuan ZOU, Auteur ; Fengjing LIANG, Auteur ; QianYing YE, Auteur ; Yijie LI, Auteur ; ShiHuan WANG, Auteur ; Kaiyun CHEN, Auteur ; Hongzhu DENG, Auteur Article en page(s) : p.e70219 Langues : Anglais (eng) Mots-clés : autism  autism symptoms  broader autism phenotype  early life  overlap Index. décimale : PER Périodiques Résumé : ABSTRACT Several studies have examined trajectories of autism symptoms in autistic children and their siblings. However, less is known about developmental patterns across different neurodevelopmental conditions, as well as the clinical characteristics and early predictors among children with distinct diagnoses but overlapping trajectories. This study investigated trajectories of autism symptoms [ADOS-2 Calibrated Severity Score; Total CSS, social affect (SA) CSS, and restricted and repetitive behaviors (RRB) CSS] and their overlap across symptom domains in a Chinese cohort of 163 children aged 18?36?months, including autism, broader autism phenotype (BAP), developmental delay (DD), and typical development (TD). Latent class growth modeling identified three trajectories for Total CSS and SA CSS, and two for RRB CSS. Cross-domain analyses revealed overlapping CSS trajectories between 51 autistic children (Overlap-Autism) and 36 children with BAP (Overlap-BAP). Clinical comparisons between these two groups revealed distinct temporal profiles in CSS and ADI-R scores. Hierarchical logistic regression analyses indicated that female sex was a protective factor for Overlap-Autism (OR?=?0.20, p?=?0.009) relative to the Overlap-BAP group, whereas higher SA CSS at 18?months independently predicted Overlap-Autism (OR?=?1.61, p?=?0.003). These findings highlight the challenges of early diagnostic differentiation among children with autism-related traits and underscore the importance of comprehensive and longitudinal assessment. En ligne : https://doi.org/10.1002/aur.70219 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587 [article] Trajectories of Autism Symptoms and Overlapping Patterns in a Chinese Cohort From 18 to 36 Months [texte imprimé] / Feixia ZHANG, Auteur ; YanTing XU, Auteur ; Linru LIU, Auteur ; Yu XING, Auteur ; Cong YOU, Auteur ; ShaoLi LV, Auteur ; Huishi HUANG, Auteur ; YuanYuan ZOU, Auteur ; Fengjing LIANG, Auteur ; QianYing YE, Auteur ; Yijie LI, Auteur ; ShiHuan WANG, Auteur ; Kaiyun CHEN, Auteur ; Hongzhu DENG, Auteur . - p.e70219. Langues : Anglais (eng) in Autism Research > 19-5 (May 2026) . - p.e70219 Mots-clés : autism  autism symptoms  broader autism phenotype  early life  overlap Index. décimale : PER Périodiques Résumé : ABSTRACT Several studies have examined trajectories of autism symptoms in autistic children and their siblings. However, less is known about developmental patterns across different neurodevelopmental conditions, as well as the clinical characteristics and early predictors among children with distinct diagnoses but overlapping trajectories. This study investigated trajectories of autism symptoms [ADOS-2 Calibrated Severity Score; Total CSS, social affect (SA) CSS, and restricted and repetitive behaviors (RRB) CSS] and their overlap across symptom domains in a Chinese cohort of 163 children aged 18?36?months, including autism, broader autism phenotype (BAP), developmental delay (DD), and typical development (TD). Latent class growth modeling identified three trajectories for Total CSS and SA CSS, and two for RRB CSS. Cross-domain analyses revealed overlapping CSS trajectories between 51 autistic children (Overlap-Autism) and 36 children with BAP (Overlap-BAP). Clinical comparisons between these two groups revealed distinct temporal profiles in CSS and ADI-R scores. Hierarchical logistic regression analyses indicated that female sex was a protective factor for Overlap-Autism (OR?=?0.20, p?=?0.009) relative to the Overlap-BAP group, whereas higher SA CSS at 18?months independently predicted Overlap-Autism (OR?=?1.61, p?=?0.003). These findings highlight the challenges of early diagnostic differentiation among children with autism-related traits and underscore the importance of comprehensive and longitudinal assessment. En ligne : https://doi.org/10.1002/aur.70219 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587

---

1 (1 - 3 / 3) Par page : 25 50 100 200