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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
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.
Abstract:
Schizophrenia exhibits substantial clinical and neuroanatomical heterogeneity, yet conventional cross-sectional studies typically analyse patients at different disease stages as homogeneous groups, diluting pathological diversity. We applied the Subtype and Stage Inference (SuStaIn) algorithm to structural MRI data from 85 patients with schizophrenia and 224 healthy controls, integrating this with resting-state functional MRI analysis for the first time. SuStaIn identified two distinct neuroanatomical subtypes: Subtype0 demonstrated anterior-to-posterior progression with early frontal-limbic atrophy and prominent positive symptoms, while Subtype1 exhibited posterior-to-anterior progression originating in subcortical-occipital regions with greater social withdrawal. Disease progression stage correlated with functional connectivity in opposing directions-Subtype0 showed hypoconnectivity (ρ = -0.56) while Subtype1 exhibited hyperconnectivity (ρ = 0.70). These contrasting patterns may explain decades of contradictory functional connectivity findings in schizophrenia literature, as previous studies likely captured different subtypes at various disease stages. Our integrated structure-function approach reveals distinct disease trajectories that could inform subtype-specific therapeutic strategies.

