Evidence map›Paper›PMID 42853485›Full record

ArticleBrain imaging and behavior2026

Gray matter subtyping with SuStaIn reveals neuroanatomical patterns in autism spectrum disorder.

Hao Ren, Yumei Duan, Hechun Li, Sisi Jiang, Jianwei Zhang, Meropi Pavlidou, Roberto Rodriguez-Labrada, Tao Peng, Cheng Luo, Chang Liu

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Article in Brain imaging and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Hao RenCollege of Computer Science, Chengdu University, Chengdu, 610106, P. R. China.
Yumei DuanDepartment of Computer and Software, Chengdu Jincheng College, Chengdu, P. R. China.
Hechun LiThe Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Sisi JiangThe Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Jianwei ZhangCollege of Computer Science, Chengdu University, Chengdu, 610106, P. R. China.
Meropi PavlidouStirling College, Chengdu University, Chengdu, 610106, P. R. China.
Roberto Rodriguez-LabradaCuban Neuroscience Center, La Habana, Cuba.
Tao PengAffiliated Hospital of Chengdu University, Chengdu, 610106, P. R. China.
Cheng LuoThe Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China. chengluo@uestc.edu.cn.
Chang LiuCollege of Computer Science, Chengdu University, Chengdu, 610106, P. R. China. liuchang@cdu.edu.cn.

Funding

Key Laboratory of Digital Innovation of Tianfu Culture, Sichuan Provincial Department of Culture and Tourism Tianfu Jincheng Laboratory 2025ZH013National Key R&D Program of China 2024YFE0215100National Natural Science Foundation of China 62406043Natural Science Foundation of Sichuan Province 24NSFSC2722
6 · The paper itself

Abstract

Autism spectrum disorder (ASD) is highly heterogeneous, and structural magnetic resonance imaging (MRI) studies have reported both increased and decreased gray matter volume relative to typically developing controls. This variability may obscure distinct neuroanatomical patterns in conventional group-level analyses. It therefore motivates subtyping approaches that can characterize neuroanatomical heterogeneity beyond conventional group-level analyses. We applied Subtype and Stage Inference (SuStaIn) to structural MRI data from the Autism Brain Imaging Data Exchange (ABIDE) to identify gray matter subtypes and stage-like variation in ASD. Original and sign-reversed z-score representations were modeled to capture gray matter deviations above and below the control reference. We then evaluated whether the organization of subtype-related brain regions was consistent across deviation directions. Cross-direction consistency, within-ABIDE cross-cohort separability, and structural covariance network (SCN) differences between stage groups were assessed using subtype alignment, Dice coefficients, cross-cohort machine-learning classification, and structural covariance analyses. We identified two gray matter subtype patterns in ASD that were consistent across deviation directions. Subtype 1 was centered on cerebellar-limbic-striatal regions, whereas Subtype 2 involved anterior fronto-cingulo-insular regions. In exploratory covariate-adjusted analyses, higher stage in sign-reversed-model S1 was associated with lower verbal intelligence quotient (IQ) scores, whereas S2 showed modestly higher Autism Diagnostic Observation Schedule (ADOS) scores. The two subtypes showed regionally distinct volume profiles. The two-subtype solution showed strong cross-direction agreement, and within-ABIDE cross-cohort classification supported structural separability of the aligned subtypes. In the sign-reversed model, SCN analyses further identified stage-group structural covariance differences within each subtype, with little evidence for a stable covariance difference between subtypes. This study identifies two gray matter-based ASD subtype patterns that were consistent across the original and sign-reversed z-score representations, with distinct regional volume profiles, selective clinical associations, and stage-group structural covariance differences. The findings provide a neuroanatomical framework for organizing ASD heterogeneity and for examining brain-behavior variation in future studies.

Indexed as

Autism Spectrum DisorderBrainGray MatterAdolescentBrain MappingChildFemaleHumansImage Processing, Computer-AssistedMachine LearningMagnetic Resonance ImagingMaleAutism spectrum disorderGray matter volumeNeuroanatomical subtypingSubtype and stage inferenceSupport vector machine

Identifiers

PMID42853485

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.