ArticleMolecular autism2023
Developmental prediction modeling based on diffusion tensor imaging uncovering age-dependent heterogeneity in early childhood autistic brain.
Article in Molecular autism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02807766 (Brain Plasticity of Autism in Response to Early Behavioral Intervention), which is not on this map. Cited by 10 papers.
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The trial behind it
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Brain Plasticity of Autism in Response to Early Behavioral Intervention: A Multimodal MRI Study
Who cites it
10 citing papers in PubMed.
- From heterogeneity to translation: data‑driven subtyping of autism in a multilevel framework.Translational psychiatry · 2026Review
- Impact of screen time on white matter integrity and neurodevelopment in children with autism spectrum disorder: a diffusional kurtosis imaging mediation analysis.European child & adolescent psychiatry · 2026Article
- A two-step temporal data augmentation and supervised learning framework for predicting autism diagnosis at 36 months in patients with tuberous sclerosis complex.Computers in biology and medicine · 2026Article
- Subtyping Autism Spectrum Disorder With a Population Graph-Based Dual Autoencoder: Revealing Two Distinct Biotypes.CNS neuroscience & therapeutics · 2025Article
- Diffusion trajectory of atypical morphological development in autism spectrum disorder.Communications biology · 2025Article
- Leveraging AI-Driven Neuroimaging Biomarkers for Early Detection and Social Function Prediction in Autism Spectrum Disorders: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Alterations in the white matter fiber tracts of preschool-aged children with autism spectrum disorder: an automated fiber quantification study.Quantitative imaging in medicine and surgery · 2024Article
- Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder.Molecular autism · 2024Article
- Individual Deviation-Based Functional Hypergraph for Identifying Subtypes of Autism Spectrum Disorder.Brain sciences · 2024Article
- Utilizing typical developmental trajectories to reflect brain abnormalities in autism spectrum disorder.Psychoradiology · 2024Article
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Authors and funding
14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveThere 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.
methodIn 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.
resultsWe 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.
conclusionThis 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 ).
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