Work

Mapping topological abnormalities in cortical similarity networks to schizophrenia-associated gene expression

Year: 2026

Type: article

Abstract: INTRODUCTION: Disrupted structural connectivity is recognized as a key pathophysiological feature of schizophrenia (SCZ). However, the relationship between cortical similarity network alterations and gene expression remains poorly understood. METHODS: We applied the Morphometric INverse Divergence framework to T1-weighted MRI from 1,216 participants. Cortical similarity networks were constructed, and global and nodal metrics were computed. Case-control comparisons were performed using linear models. Partial least squares (PLS) regression identified genes associated with spatial patterns of network alterations using Allen Human Brain Atlas data. RESULTS: Among global metrics, only the rich-club coefficient differed between groups, with a negligible effect size. Nodal metrics showed reduced eigenvector centrality and k-coreness centrality in left temporal/insular (somatomotor), lateral occipital (visual), anterior cingulate (salience/ventral attention), and posterior cingulate (default mode) regions. Participation coefficient was widely reduced in SCZ. For each nodal metric, we identified PLS2-positive and PLS2-negative gene sets. Across degree, eigenvector centrality, and k-coreness centrality, PLS2-negative genes were enriched for metal ion transport, linked to manic and nonorganic psychosis, and upregulated in adolescence and early adulthood. PLS2-positive genes were enriched for neuron projection development and learning or memory, but not psychotic disorders. CONCLUSIONS: These findings highlight synaptic and neurodevelopmental mechanisms underlying structural dysconnectivity in SCZ.

Source: Dialogues in Clinical Neuroscience

DOI: 10.1080/19585969.2026.2682773

Authors: Sung Woo Joo, Jungsun Lee

Institutions: Asan Medical Center, University of Ulsan

Language: English

Topic: Functional Brain Connectivity Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: diamond

Funders: National Research Foundation, Korea Health Industry Development Institute