Patients with schizophrenia experience accelerated aging, accompanied by abnormalities in biomarkers such as shorter telomere length. Brain age prediction using neuroimaging data has gained attention in schizophrenia research, with consistently reported increases in brain-predicted age difference (brain-PAD). However, its associations with clinical symptoms and illness duration remain unclear.

We developed brain age prediction models using structural magnetic resonance imaging (MRI) data from 10,938 healthy individuals. The models were validated on an independent test dataset comprising 79 healthy controls, 57 patients with recent-onset schizophrenia, and 71 patients with chronic schizophrenia. Group comparisons and the clinical associations of brain-PAD were analyzed using multiple linear regression. SHapley Additive exPlanations (SHAP) values estimated feature contributions to the model, and between-group differences in SHAP values and group-by-SHAP value interactions were also examined.

Patients with recent-onset schizophrenia and chronic schizophrenia exhibited increased brain-PAD values of 1.2 and 0.9 years, respectively. Between-group differences in SHAP values were identified in the right lateral prefrontal area (false discovery rate [FDR] p = 0.022), with group-by-SHAP value interactions observed in the left prefrontal area (FDR p = 0.049). A negative association between brain-PAD and Full-scale Intelligence Quotient scores in chronic schizophrenia was noted, which did not remain significant after correction for multiple comparisons.

Brain-PAD increases were pronounced in the early phase of schizophrenia. Regional brain abnormalities contributing to brain-PAD likely vary with illness duration. Future longitudinal studies are required to overcome limitations related to sample size, heterogeneity, and the cross-sectional design of this study.

White matter disruptions in schizophrenia have been widely reported, but it remains unclear whether these abnormalities differ between illness stages. We mapped the connectome in patients with recently diagnosed and chronic schizophrenia and investigated the extent and overlap of white matter connectivity disruptions between these illness stages.

Diffusion-weighted magnetic resonance images were acquired in recent-onset (n = 19) and chronic patients (n = 45) with schizophrenia, as well as age-matched controls (n = 87). Whole-brain fiber tracking was performed to quantify the strength of white matter connections. Connections were tested for significant streamline count reductions in recent-onset and chronic groups, relative to separate age-matched controls. Permutation tests were used to assess whether disrupted connections significantly overlapped between chronic and recent-onset patients. Linear regression was performed to test whether connectivity was strongest in controls, weakest in chronic patients, and midway between these extremities in recent-onset patients (controls > recent-onset > chronic).

Compared with controls, chronic patients displayed a widespread network of connectivity disruptions (p < 0.01). In contrast, connectivity reductions were circumscribed to the anterior fibers of the corpus callosum in recent-onset patients (p < 0.01). A significant proportion of disrupted connections in recent-onset patients (86%) coincided with disrupted connections in chronic patients (p < 0.01). Linear regression revealed that chronic patients displayed reduced connectivity relative to controls, while recent-onset patients showed an intermediate reduction compared with chronic patients (p < 0.01).

Connectome pathology in recent-onset patients with schizophrenia is confined to select tracts within a more extensive network of white matter connectivity disruptions found in chronic illness. These findings may suggest a trajectory of progressive deterioration of connectivity in schizophrenia.