Examinations of the heterogeneity in the structural brain connectome in schizophrenia.
Authors
Affiliations (7)
Affiliations (7)
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.
- Schizophrenia Imaging Lab, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.
- Department of Radiology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710004, China.
- Department of Psychiatry, Xi'an Gaoxin Hospital, Xi'an, Shaanxi, 710075, China.
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.
- Queen Mary School Hainan, Beijing University of Posts and Telecommunications, Lingshui, Hainan, 572423, China.
Abstract
Schizophrenia (SCZ) is a heterogeneous disorder characterized by widespread brain dysconnectivity, yet it remains unclear whether variable structural dysconnectivity patterns reflect biologically and clinically meaningful subtypes. We recruited 105 SCZ patients and 97 healthy controls, collecting magnetic resonance imaging, clinical assessment, and laboratory test data. Double generalized linear models were first applied to estimate group differences in the mean and inter-individual variability of structural connectivity between SCZ and controls. Subsequently, nonnegative matrix factorization was used to identify SCZ subtypes according to dysconnectivity profiles. We observed a significantly altered subnetwork that exhibited increased inter-individual variability in SCZ, with its connections and regions predominantly enriched in the ventral-attention, frontal-parietal, and default-mode networks that support higher-order cognition. Connectivity-derived subtype analysis grouped patients into two subtypes, with subtype-II tending to show more severe positive symptoms (<i>t</i> = 2.272, nominal <i>P</i> = 0.025), a lower neutrophil/lymphocyte ratio (<i>t</i> = -2.383, nominal <i>P</i> = 0.025), a better treatment response (<i>t</i> = 2.366, nominal <i>P</i> = 0.021), and greater short-term symptom improvement (<i>t</i> = 3.509, nominal <i>P</i> = 0.006) within the olanzapine monotherapy subgroup. This subtype also demonstrated distinct neuroanatomical features, including a subtype-specific cortical thickness change pattern unrelated to SCZ or bipolar disorder, as well as subtype-specific brain epicenters, such as left posterior cingulate and rostral middle frontal regions. Our study demonstrates increased inter-individual variability in the structural connectome of SCZ and highlights the potential of connectome-based subtyping approaches for characterizing disease heterogeneity related to pathophysiological processes.