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Cross-disorder brain morphological similarity in schizophrenia: Associations with symptom severity and treatment
Yongbin Wei1, Yanmeng Huang1, Huiru Cui2
1Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
Background:
Schizophrenia (SCZ) exhibits considerable overlap with other psychiatric disorders in clinical symptoms and brain structural abnormalities, yet the relationship between these shared neuroanatomical patterns and individual clinical manifestations remains poorly understood.
Methods:
We conducted a longitudinal study of 100 first-episode SCZ patients and 97 healthy controls (HCs), acquiring structural magnetic resonance imaging data at baseline and post antipsychotic treatment. Using normative modeling and summary statistics from eight psychiatric disorders, we computed a cross-disorder regional vulnerability index (RVI) that captures morphological similarity patterns across eight psychiatric disorders at the individual level.
Results:
We found that SCZ patients demonstrated the highest RVI to bipolar disorder, major depressive disorder, and obsessive-compulsive disorder, with similarity levels increasing over the disease course. Cross-disorder RVI effectively discriminated SCZ patients from HCs, achieving classification accuracies of 0.83 at baseline and 0.87 at follow-up. Particularly, cross-disorder RVIs significantly correlated with symptom severity (p = 0.005), revealing divergent associations between positive and negative syndrome scales. Baseline cross-disorder RVI also predicted the improvement of negative syndrome following antipsychotic treatment (p = 0.021).
Conclusions:
These findings highlight the potential of cross-disorder brain similarity profiling to improve personalized diagnosis and treatment in individuals with SCZ.
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