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Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain / Yating MING ; Weixing ZHAO ; Rui FENG ; Yuanyue ZHOU ; Lijie WU ; Jia WANG ; Jinming XIAO ; Lei LI ; Xiaolong SHAN ; Jing CAO ; Xiaodong KANG ; Huafu CHEN ; Xujun DUAN in Molecular Autism, 14 (2023)
[article]
Titre : Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain Type de document : Texte imprimé et/ou numérique Auteurs : Yating MING, Auteur ; Weixing ZHAO, Auteur ; Rui FENG, Auteur ; Yuanyue ZHOU, Auteur ; Lijie WU, Auteur ; Jia WANG, Auteur ; Jinming XIAO, Auteur ; Lei LI, Auteur ; Xiaolong SHAN, Auteur ; Jing CAO, Auteur ; Xiaodong KANG, Auteur ; Huafu CHEN, Auteur ; Xujun DUAN, Auteur Article en page(s) : 41 p. Langues : Anglais (eng) Mots-clés : Child Humans Child, Preschool Diffusion Tensor Imaging/methods *Autistic Disorder/diagnostic imaging Brain/diagnostic imaging *White Matter/diagnostic imaging Cluster Analysis Index. décimale : PER Périodiques Résumé : OBJECTIVE: There has been increasing evidence for atypical white matter (WM) microstructure in autistic people, but findings have been divergent. The development of autistic people in early childhood is clouded by the concurrently rapid brain growth, which might lead to the inconsistent findings of atypical WM microstructure in autism. Here, we aimed to reveal the developmental nature of autistic children and delineate atypical WM microstructure throughout early childhood while taking developmental considerations into account. METHOD: In this study, diffusion tensor imaging was acquired from two independent cohorts, containing 91 autistic children and 100 typically developing children (TDC), aged 4-7 years. Developmental prediction modeling using support vector regression based on TDC participants was conducted to estimate the WM atypical development index of autistic children. Then, subgroups of autistic children were identified by using the k-means clustering method and were compared to each other on the basis of demographic information, WM atypical development index, and autistic trait by using two-sample t-test. Relationship of the WM atypical development index with age was estimated by using partial correlation. Furthermore, we performed threshold-free cluster enhancement-based two-sample t-test for the group comparison in WM microstructures of each subgroup of autistic children with the rematched subsets of TDC. RESULTS: We clustered autistic children into two subgroups according to WM atypical development index. The two subgroups exhibited distinct developmental stages and age-dependent diversity. WM atypical development index was found negatively associated with age. Moreover, an inverse pattern of atypical WM microstructures and different clinical manifestations in the two stages, with subgroup 1 showing overgrowth with low level of autistic traits and subgroup 2 exhibiting delayed maturation with high level of autistic traits, were revealed. CONCLUSION: This study illustrated age-dependent heterogeneity in early childhood autistic children and delineated developmental stage-specific difference that ranged from an overgrowth pattern to a delayed pattern. Trial registration This study has been registered at ClinicalTrials.gov (Identifier: NCT02807766) on June 21, 2016 ( https://clinicaltrials.gov/ct2/show/NCT02807766 ). En ligne : https://dx.doi.org/10.1186/s13229-023-00573-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518
in Molecular Autism > 14 (2023) . - 41 p.[article] Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain [Texte imprimé et/ou numérique] / Yating MING, Auteur ; Weixing ZHAO, Auteur ; Rui FENG, Auteur ; Yuanyue ZHOU, Auteur ; Lijie WU, Auteur ; Jia WANG, Auteur ; Jinming XIAO, Auteur ; Lei LI, Auteur ; Xiaolong SHAN, Auteur ; Jing CAO, Auteur ; Xiaodong KANG, Auteur ; Huafu CHEN, Auteur ; Xujun DUAN, Auteur . - 41 p.
Langues : Anglais (eng)
in Molecular Autism > 14 (2023) . - 41 p.
Mots-clés : Child Humans Child, Preschool Diffusion Tensor Imaging/methods *Autistic Disorder/diagnostic imaging Brain/diagnostic imaging *White Matter/diagnostic imaging Cluster Analysis Index. décimale : PER Périodiques Résumé : OBJECTIVE: There has been increasing evidence for atypical white matter (WM) microstructure in autistic people, but findings have been divergent. The development of autistic people in early childhood is clouded by the concurrently rapid brain growth, which might lead to the inconsistent findings of atypical WM microstructure in autism. Here, we aimed to reveal the developmental nature of autistic children and delineate atypical WM microstructure throughout early childhood while taking developmental considerations into account. METHOD: In this study, diffusion tensor imaging was acquired from two independent cohorts, containing 91 autistic children and 100 typically developing children (TDC), aged 4-7 years. Developmental prediction modeling using support vector regression based on TDC participants was conducted to estimate the WM atypical development index of autistic children. Then, subgroups of autistic children were identified by using the k-means clustering method and were compared to each other on the basis of demographic information, WM atypical development index, and autistic trait by using two-sample t-test. Relationship of the WM atypical development index with age was estimated by using partial correlation. Furthermore, we performed threshold-free cluster enhancement-based two-sample t-test for the group comparison in WM microstructures of each subgroup of autistic children with the rematched subsets of TDC. RESULTS: We clustered autistic children into two subgroups according to WM atypical development index. The two subgroups exhibited distinct developmental stages and age-dependent diversity. WM atypical development index was found negatively associated with age. Moreover, an inverse pattern of atypical WM microstructures and different clinical manifestations in the two stages, with subgroup 1 showing overgrowth with low level of autistic traits and subgroup 2 exhibiting delayed maturation with high level of autistic traits, were revealed. CONCLUSION: This study illustrated age-dependent heterogeneity in early childhood autistic children and delineated developmental stage-specific difference that ranged from an overgrowth pattern to a delayed pattern. Trial registration This study has been registered at ClinicalTrials.gov (Identifier: NCT02807766) on June 21, 2016 ( https://clinicaltrials.gov/ct2/show/NCT02807766 ). En ligne : https://dx.doi.org/10.1186/s13229-023-00573-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518 Age-related changes in neural responses to sensory stimulation in autism: a cross-sectional study / Kaitlin K. CUMMINGS ; Susan Y. BOOKHEIMER ; Mirella DAPRETTO ; Shulamite A. GREEN in Molecular Autism, 14 (2023)
[article]
Titre : Age-related changes in neural responses to sensory stimulation in autism: a cross-sectional study Type de document : Texte imprimé et/ou numérique Auteurs : Kaitlin K. CUMMINGS, Auteur ; Susan Y. BOOKHEIMER, Auteur ; Mirella DAPRETTO, Auteur ; Shulamite A. GREEN, Auteur Article en page(s) : 38 p. Langues : Anglais (eng) Mots-clés : Adolescent Child Humans *Autistic Disorder/diagnostic imaging *Autism Spectrum Disorder Cross-Sectional Studies Prefrontal Cortex/diagnostic imaging Cerebellum Magnetic Resonance Imaging/methods Autism spectrum disorder Development Neural activity Sensory over-responsivity Sensory processing fMRI Index. décimale : PER Périodiques Résumé : BACKGROUND: Sensory over-responsivity (SOR) is an impairing sensory processing challenge in autism spectrum disorder (ASD) which shows heterogenous developmental trajectories and appears to improve into adulthood in some but not all autistic individuals. However, the neural mechanisms underlying interindividual differences in these trajectories are currently unknown. METHODS: Here, we used functional magnetic resonance imaging (fMRI) to investigate the association between age and neural activity linearly and nonlinearly in response to mildly aversive sensory stimulation as well as how SOR severity moderates this association. Participants included 52 ASD (14F) and 41 (13F) typically developing (TD) youth, aged 8.6-18.0 years. RESULTS: We found that in pre-teens, ASD children showed widespread activation differences in sensorimotor, frontal and cerebellar regions compared to TD children, while there were fewer differences between ASD and TD teens. In TD youth, older age was associated with less activation in the prefrontal cortex. In contrast, in ASD youth, older age was associated with more engagement of sensory integration and emotion regulation regions. In particular, orbitofrontal and medial prefrontal cortices showed a nonlinear relationship with age in ASD, with an especially steep increase in sensory-evoked neural activity during the mid-to-late teen years. There was also an interaction between age and SOR severity in ASD youth such that these age-related trends were more apparent in youth with higher SOR. LIMITATIONS: The cross-sectional design limits causal interpretations of the data. Future longitudinal studies will be instrumental in determining how prefrontal engagement and SOR co-develop across adolescence. CONCLUSIONS: Our results suggest that enhanced recruitment of prefrontal regions may underlie age-related decreases in SOR for a subgroup of ASD youth. En ligne : https://dx.doi.org/10.1186/s13229-023-00571-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518
in Molecular Autism > 14 (2023) . - 38 p.[article] Age-related changes in neural responses to sensory stimulation in autism: a cross-sectional study [Texte imprimé et/ou numérique] / Kaitlin K. CUMMINGS, Auteur ; Susan Y. BOOKHEIMER, Auteur ; Mirella DAPRETTO, Auteur ; Shulamite A. GREEN, Auteur . - 38 p.
Langues : Anglais (eng)
in Molecular Autism > 14 (2023) . - 38 p.
Mots-clés : Adolescent Child Humans *Autistic Disorder/diagnostic imaging *Autism Spectrum Disorder Cross-Sectional Studies Prefrontal Cortex/diagnostic imaging Cerebellum Magnetic Resonance Imaging/methods Autism spectrum disorder Development Neural activity Sensory over-responsivity Sensory processing fMRI Index. décimale : PER Périodiques Résumé : BACKGROUND: Sensory over-responsivity (SOR) is an impairing sensory processing challenge in autism spectrum disorder (ASD) which shows heterogenous developmental trajectories and appears to improve into adulthood in some but not all autistic individuals. However, the neural mechanisms underlying interindividual differences in these trajectories are currently unknown. METHODS: Here, we used functional magnetic resonance imaging (fMRI) to investigate the association between age and neural activity linearly and nonlinearly in response to mildly aversive sensory stimulation as well as how SOR severity moderates this association. Participants included 52 ASD (14F) and 41 (13F) typically developing (TD) youth, aged 8.6-18.0 years. RESULTS: We found that in pre-teens, ASD children showed widespread activation differences in sensorimotor, frontal and cerebellar regions compared to TD children, while there were fewer differences between ASD and TD teens. In TD youth, older age was associated with less activation in the prefrontal cortex. In contrast, in ASD youth, older age was associated with more engagement of sensory integration and emotion regulation regions. In particular, orbitofrontal and medial prefrontal cortices showed a nonlinear relationship with age in ASD, with an especially steep increase in sensory-evoked neural activity during the mid-to-late teen years. There was also an interaction between age and SOR severity in ASD youth such that these age-related trends were more apparent in youth with higher SOR. LIMITATIONS: The cross-sectional design limits causal interpretations of the data. Future longitudinal studies will be instrumental in determining how prefrontal engagement and SOR co-develop across adolescence. CONCLUSIONS: Our results suggest that enhanced recruitment of prefrontal regions may underlie age-related decreases in SOR for a subgroup of ASD youth. En ligne : https://dx.doi.org/10.1186/s13229-023-00571-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518 Exploring the multidimensional nature of repetitive and restricted behaviors and interests (RRBI) in autism: neuroanatomical correlates and clinical implications / Nicolas TRAUT ; Amandine PEDOUX ; Anna MARUANI ; Anita BEGGIATO ; Monique ELMALEH ; David GERMANAUD ; Anouck AMESTOY ; Myriam LY-LE MOAL ; Christopher CHATHAM ; Lorraine MURTAGH ; Manuel BOUVARD ; Marianne ALISSON ; Marion LEBOYER ; Thomas BOURGERON ; Roberto TORO ; Guillaume DUMAS ; Clara MOREAU ; Richard DELORME in Molecular Autism, 14 (2023)
[article]
Titre : Exploring the multidimensional nature of repetitive and restricted behaviors and interests (RRBI) in autism: neuroanatomical correlates and clinical implications Type de document : Texte imprimé et/ou numérique Auteurs : Nicolas TRAUT, Auteur ; Amandine PEDOUX, Auteur ; Anna MARUANI, Auteur ; Anita BEGGIATO, Auteur ; Monique ELMALEH, Auteur ; David GERMANAUD, Auteur ; Anouck AMESTOY, Auteur ; Myriam LY-LE MOAL, Auteur ; Christopher CHATHAM, Auteur ; Lorraine MURTAGH, Auteur ; Manuel BOUVARD, Auteur ; Marianne ALISSON, Auteur ; Marion LEBOYER, Auteur ; Thomas BOURGERON, Auteur ; Roberto TORO, Auteur ; Guillaume DUMAS, Auteur ; Clara MOREAU, Auteur ; Richard DELORME, Auteur Article en page(s) : 45 p. Langues : Anglais (eng) Mots-clés : Humans *Autistic Disorder/diagnostic imaging *Autism Spectrum Disorder/diagnosis Neuroanatomy Magnetic Resonance Imaging Principal Component Analysis Cortico-striatal-thalamo-cortical loop Phenotype Rrb Index. décimale : PER Périodiques Résumé : BACKGROUND: Repetitive and restricted behaviors and interests (RRBI) are core symptoms of autism with a complex entity and are commonly categorized into 'motor-driven' and 'cognitively driven'. RRBI symptomatology depends on the individual's clinical environment limiting the understanding of RRBI physiology, particularly their associated neuroanatomical structures. The complex RRBI heterogeneity needs to explore the whole RRBI spectrum by integrating the clinical context [autistic individuals, their relatives and typical developing (TD) individuals]. We hypothesized that different RRBI dimensions would emerge by exploring the whole spectrum of RRBI and that these dimensions are associated with neuroanatomical signatures-involving cortical and subcortical areas. METHOD: A sample of 792 individuals composed of 267 autistic subjects, their 370 first-degree relatives and 155 TD individuals was enrolled in the study. We assessed the whole patterns of RRBI in each individual by using the Repetitive Behavior Scale-Revised and the Yale-Brown Obsessive Compulsive Scale. We estimated brain volumes using MRI scanner for a subsample of the subjects (n=152, 42 ASD, 89 relatives and 13 TD). We first investigated the dimensionality of RRBI by performing a principal component analysis on all items of these scales and included all the sampling population. We then explored the relationship between RRBI-derived factors with brain volumes using linear regression models. RESULTS: We identified 3 main factors (with 30.3% of the RRBI cumulative variance): Factor 1 (FA1, 12.7%) reflected mainly the 'motor-driven' RRBI symptoms; Factor 2 and 3 (respectively, 8.8% and 7.9%) gathered mainly Y-BOCS related items and represented the 'cognitively driven' RRBI symptoms. These three factors were significantly associated with the right/left putamen volumes but with opposite effects: FA1 was negatively associated with an increased volume of the right/left putamen conversely to FA2 and FA3 (all uncorrected p<0.05). FA1 was negatively associated with the left amygdala (uncorrected p<0.05), and FA2 was positively associated with the left parietal structure (uncorrected p=0.001). CONCLUSION: Our results suggested 3 coherent RRBI dimensions involving the putamen commonly and other structures according to the RRBI dimension. The exploration of the putamen's integrative role in RSBI needs to be strengthened in further studies. En ligne : https://dx.doi.org/10.1186/s13229-023-00576-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518
in Molecular Autism > 14 (2023) . - 45 p.[article] Exploring the multidimensional nature of repetitive and restricted behaviors and interests (RRBI) in autism: neuroanatomical correlates and clinical implications [Texte imprimé et/ou numérique] / Nicolas TRAUT, Auteur ; Amandine PEDOUX, Auteur ; Anna MARUANI, Auteur ; Anita BEGGIATO, Auteur ; Monique ELMALEH, Auteur ; David GERMANAUD, Auteur ; Anouck AMESTOY, Auteur ; Myriam LY-LE MOAL, Auteur ; Christopher CHATHAM, Auteur ; Lorraine MURTAGH, Auteur ; Manuel BOUVARD, Auteur ; Marianne ALISSON, Auteur ; Marion LEBOYER, Auteur ; Thomas BOURGERON, Auteur ; Roberto TORO, Auteur ; Guillaume DUMAS, Auteur ; Clara MOREAU, Auteur ; Richard DELORME, Auteur . - 45 p.
Langues : Anglais (eng)
in Molecular Autism > 14 (2023) . - 45 p.
Mots-clés : Humans *Autistic Disorder/diagnostic imaging *Autism Spectrum Disorder/diagnosis Neuroanatomy Magnetic Resonance Imaging Principal Component Analysis Cortico-striatal-thalamo-cortical loop Phenotype Rrb Index. décimale : PER Périodiques Résumé : BACKGROUND: Repetitive and restricted behaviors and interests (RRBI) are core symptoms of autism with a complex entity and are commonly categorized into 'motor-driven' and 'cognitively driven'. RRBI symptomatology depends on the individual's clinical environment limiting the understanding of RRBI physiology, particularly their associated neuroanatomical structures. The complex RRBI heterogeneity needs to explore the whole RRBI spectrum by integrating the clinical context [autistic individuals, their relatives and typical developing (TD) individuals]. We hypothesized that different RRBI dimensions would emerge by exploring the whole spectrum of RRBI and that these dimensions are associated with neuroanatomical signatures-involving cortical and subcortical areas. METHOD: A sample of 792 individuals composed of 267 autistic subjects, their 370 first-degree relatives and 155 TD individuals was enrolled in the study. We assessed the whole patterns of RRBI in each individual by using the Repetitive Behavior Scale-Revised and the Yale-Brown Obsessive Compulsive Scale. We estimated brain volumes using MRI scanner for a subsample of the subjects (n=152, 42 ASD, 89 relatives and 13 TD). We first investigated the dimensionality of RRBI by performing a principal component analysis on all items of these scales and included all the sampling population. We then explored the relationship between RRBI-derived factors with brain volumes using linear regression models. RESULTS: We identified 3 main factors (with 30.3% of the RRBI cumulative variance): Factor 1 (FA1, 12.7%) reflected mainly the 'motor-driven' RRBI symptoms; Factor 2 and 3 (respectively, 8.8% and 7.9%) gathered mainly Y-BOCS related items and represented the 'cognitively driven' RRBI symptoms. These three factors were significantly associated with the right/left putamen volumes but with opposite effects: FA1 was negatively associated with an increased volume of the right/left putamen conversely to FA2 and FA3 (all uncorrected p<0.05). FA1 was negatively associated with the left amygdala (uncorrected p<0.05), and FA2 was positively associated with the left parietal structure (uncorrected p=0.001). CONCLUSION: Our results suggested 3 coherent RRBI dimensions involving the putamen commonly and other structures according to the RRBI dimension. The exploration of the putamen's integrative role in RSBI needs to be strengthened in further studies. En ligne : https://dx.doi.org/10.1186/s13229-023-00576-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=518