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Data-driven schizophrenia subtyping via brain atrophy trajectories and functional connectivity
Daisuke Yoshimaru1,2,3, Kazuya Ouchi4,5, Shuhei Shibukawa6,7,8
1Division of Regenerative Medicine, The Jikei University School of Medicine, Tokyo, 105-8461, Japan. d.marumaru@gmail.com.
Translational Psychiatry
|March 20, 2026
Summary
Schizophrenia shows diverse brain patterns. A new algorithm identified two subtypes with different progression and connectivity, suggesting tailored treatments for schizophrenia patients.
Area of Science:
- Neuroscience
- Psychiatry
- Medical Imaging
Background:
- Schizophrenia presents significant clinical and neuroanatomical variability.
- Conventional studies often overlook this heterogeneity by treating patients as a single group.
Purpose of the Study:
- To identify distinct neuroanatomical subtypes and disease trajectories in schizophrenia.
- To integrate structural and functional magnetic resonance imaging (MRI) data for a comprehensive analysis.
Main Methods:
- Applied the Subtype and Stage Inference (SuStaIn) algorithm to structural MRI data from 85 schizophrenia patients and 224 controls.
- Integrated resting-state functional MRI (fMRI) data to analyze functional connectivity patterns.
- Correlated disease progression stages with functional connectivity metrics.
Main Results:
- Identified two neuroanatomical subtypes: Subtype0 (anterior-to-posterior progression, frontal-limbic atrophy, positive symptoms) and Subtype1 (posterior-to-anterior progression, subcortical-occipital origin, social withdrawal).
- Disease progression showed opposing functional connectivity trends: hypoconnectivity in Subtype0 (ρ = -0.56) and hyperconnectivity in Subtype1 (ρ = 0.70).
Conclusions:
- Distinct neuroanatomical and functional trajectories exist within schizophrenia.
- These findings reconcile contradictory previous results and suggest potential for subtype-specific therapeutic strategies.
