ArticleMolecular autism2024
A 3D approach to understanding heterogeneity in early developing autisms.
Article in Molecular autism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Dynamic Functional Synchronization Profiles in Autism Differ by Spatial Scale and Along Hierarchical Cortical Gradients.Biological psychiatry global open science · 2026Article
- Distinct Temporal Stages of Infant Brain Processing Associate With Early Versus Later Autism Diagnosis.Developmental science · 2026Article
- Heterogeneity of Response to Early Start Denver Model: Identifying Developmental Trajectories and Predictors of Cognitive Outcomes.Autism research : official journal of the International Society for Autism Research · 2026Article
- Neural correlates of language disfunction in psychiatric disorders: a developmental perspective.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- Autism subtypes identified using cross-species functional connectivity analyses.Nature neuroscience · 2026Article
- Reduced Hand Specialization and Idiosyncratic Visuomotor Strategies in Autism During Naturalistic Object Manipulation.Autism research : official journal of the International Society for Autism Research · 2026Article
- Sub-groups of spoken language and broader communication skills in a large heterogenous cohort of minimally verbal school-age children: evidence of discrepant profiles.Molecular autism · 2026Article
- Fetal functional connectivity prospectively associates with autistic traits in toddlerhood.NeuroImage. Clinical · 2026Article
- Proportion and Profile of Autistic Children Not Acquiring Spoken Language Despite Receiving Evidence-Based Early Interventions.Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53 · 2025Article
- Protein-Altering Variants' Analysis in Autism Subgroups Uncovers Early Brain-Expressed Gene Modules Relevant to Autism Pathophysiology.Autism research : official journal of the International Society for Autism Research · 2025Article
- Biological subtyping of autism via cross-species fMRI.bioRxiv : the preprint server for biology · 2025Article
- Unlocking autism's complexity: theFrontiers in integrative neuroscience · 2024Article
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Abstract
backgroundPhenotypic heterogeneity in early language, intellectual, motor, and adaptive functioning (LIMA) features are amongst the most striking features that distinguish different types of autistic individuals. Yet the current diagnostic criteria uses a single label of autism and implicitly emphasizes what individuals have in common as core social-communicative and restricted repetitive behavior difficulties. Subtype labels based on the non-core LIMA features may help to more meaningfully distinguish types of autisms with differing developmental paths and differential underlying biology.
methodsUnsupervised data-driven subtypes were identified using stability-based relative clustering validation on publicly available Mullen Scales of Early Learning (MSEL) and Vineland Adaptive Behavior Scales (VABS) data (n = 615; age = 24-68 months) from the National Institute of Mental Health Data Archive (NDA). Differential developmental trajectories between subtypes were tested on longitudinal data from NDA and from an independent in-house dataset from UCSD. A subset of the UCSD dataset was also tested for subtype differences in functional and structural neuroimaging phenotypes and relationships with blood gene expression. The current subtyping model was also compared to early language outcome subtypes derived from past work.
resultsTwo autism subtypes can be identified based on early phenotypic LIMA features. These data-driven subtypes are robust in the population and can be identified in independent data with 98% accuracy. The subtypes can be described as Type I versus Type II autisms differentiated by relatively high versus low scores on LIMA features. These two types of autisms are also distinguished by different developmental trajectories over the first decade of life. Finally, these two types of autisms reveal striking differences in functional and structural neuroimaging phenotypes and their relationships with gene expression and may highlight unique biological mechanisms. LIMITATIONS: Sample sizes for the neuroimaging and gene expression dataset are relatively small and require further independent replication. The current work is also limited to subtyping based on MSEL and VABS phenotypic measures.
conclusionsThis work emphasizes the potential importance of stratifying autism by a Type I versus Type II distinction focused on LIMA features and which may be of high prognostic and biological significance.
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