Progressive brain abnormalities in schizophrenia across different illness periods: a structural and functional MRI study

Abstract

Schizophrenia is a chronic brain disorder, and neuroimaging abnormalities have been reported in different stages of the illness for decades. However, when and how these brain abnormalities occur and evolve remains undetermined. We hypothesized structural and functional brain abnormalities progress throughout the illness course at different rates in schizophrenia. A total of 115 patients with schizophrenia were recruited and stratified into three groups of different illness periods: 5-year group (illness duration: ≤5 years), 15-year group (illness duration: 12–18 years), and 25-year group (illness duration: ≥25 years); 230 healthy controls were matched by age and sex to the three groups, respectively. All participants underwent resting-state MRI scanning. Each group of patients with schizophrenia was compared with the corresponding controls in terms of voxel-based morphometry (VBM), fractional anisotropy (FA), global functional connectivity density (gFCD), and sample entropy (SampEn) abnormalities. In the 5-year group we observed only SampEn abnormalities in the putamen. In the 15-year group, we observed VBM abnormalities in the insula and cingulate gyrus and gFCD abnormalities in the temporal cortex. In the 25-year group, we observed FA abnormalities in nearly all white matter tracts, and additional VBM and gFCD abnormalities in the frontal cortex and cerebellum. By using two structural and two functional MRI analysis methods, we demonstrated that individual functional abnormalities occur in limited brain areas initially, functional connectivity and gray matter density abnormalities ensue later in wider brain areas, and structural connectivity abnormalities involving almost all white matter tracts emerge in the third decade of the course in schizophrenia.

Unveiling the potential of machine learning in schizophrenia diagnosis: A meta‐analytic study of task‐based neuroimaging data

“…Several reasons may explain this finding. First, long DOI is associated with more severe alterations in brain structure and function in SCZ, 50,51 which is consistent with both the neurodevelopmental and neurodegenerative theories of SCZ 52,53 . For instance, a 10-year follow-up study found that patients with SCZ exhibited a progressive decline in intelligence and specific neurocognitive domains, including verbal knowledge and memory, following the onset of the illness.…”

Low‐frequency rTMS induces modifications in cortical structural connectivity ‐ functional connectivity coupling in schizophrenia patients with auditory verbal hallucinations

“…Nonetheless, schizophrenia patients have also been shown to have higher whole brain SC‐FC couplings (van den Heuvel et al, 2013 ). This disparity may result from the complex neurological disease pathways that are affected by variables such as the length of the illness (Shen et al, 2023 ) and the use of antipsychotic medications (Abbott et al, 2013 ). Variations may also be introduced by different approaches to aligning SC with FC, such as correlation‐based FC or precision‐based FC (Huang & Ding, 2015 ; Liégeois et al, 2020 ).…”

“…This could result in internal dialogues being mistakenly identified as external, which would ground the symptoms seen in AVH and schizophrenia. Nonetheless, schizophrenia patients as the length of the illness (Shen et al, 2023) and the use of antipsychotic medications (Abbott et al, 2013). Variations may also be introduced by different approaches to aligning SC with FC, such as correlation-based FC or precision-based FC (Huang & Ding, 2015;Liégeois et al, 2020).…”

Thoughtful Response on “MRI-based Texture Analysis for Preoperative Prediction of BRAF V600E Mutation in Papillary Thyroid Carcinoma” [Letter]

“…1 , 2 Clinical examination such as magnetic resonance imaging (MRI) has been found to be helpful and useful clinically for detecting the structure abnormalities in certain diseases, such as schizophrenia, the chronic brain disorder. 3 In addition, MRI has been developed and utilized for the texture analysis in discrimination of tumors in patients diagnosed with medulloblastoma. 4 In the work reported by Zheng et al, an MRI-based texture feature model was utilized to provide a new approach for noninvasive and preoperative identification of BRAF V600E mutation and to find the mutation location in the tissue.…”