Abstract
Background: Despite its benefits, a major concern regarding antipsychotic treatment is its possible impact on the brain’s structure and function. This study sought to explore the characteristics of white matter structural networks in chronic never-treated schizophrenia and those treated with clozapine or risperidone, and its potential association with cognitive function. Methods: Diffusion tensor imaging was performed on a unique sample of 34 schizophrenia patients treated with antipsychotic monotherapy for over 5 years (17 treated with clozapine and 17 treated with risperidone), 17 never-treated schizophrenia patients with illness duration over 5 years, and 27 healthy control participants. Graph theory and network-based statistic approaches were employed. Results: We observed a disrupted organization of white matter structural networks as well as decreased nodal and connectivity characteristics across the schizophrenia groups, mainly involving thalamus, prefrontal, and occipital regions. Alterations in nodal and connectivity characteristics were relatively milder in risperidone-treated patients than clozapine-treated patients and never-treated patients. Altered global network measures were significantly associated with cognitive performance levels. Structural connectivity as reflected by network-based statistic mediated the difference in cognitive performance levels between clozapine-treated and risperidone-treated patients. Limitations: These results are constrained by the lack of random assignment to different types of antipsychotic treatment. Conclusion: These findings provide insight into the white matter structural network deficits in patients with chronic schizophrenia, either being treated or untreated, and suggest white matter structural networks supporting cognitive function may benefit from antipsychotic treatment, especially in those treated with risperidone.
| Originalsprache | Englisch |
|---|---|
| Zeitschrift | International Journal of Neuropsychopharmacology |
| Jahrgang | 23 |
| Ausgabenummer | 12 |
| Seiten (von - bis) | 799-810 |
| Seitenumfang | 12 |
| ISSN | 1461-1457 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 01.12.2020 |
Fördermittel
This study was supported by the National Natural Science Foundation of China (grants 81671664, 81761128023, 81901702, and 81901705); grants from the Humboldt Foundation (Ref 3.5-1206715-CHN-BES, Ref 3.5-CHN-1207072-HFST-P); Science-Technology Support Plan Projects of Sichuan Province (No. 2020YFS0117); and 1.3.5 project for disciplines of excellence, Post-Doctor Research Project, West China Hospital, Sichuan University (grants 2018HXBH05, ZYJC18020, and ZYYC08001). Interest Statement: None.
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
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SDG 3 – Gesundheit und Wohlergehen
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SDG 10 – Weniger Ungleichheiten
Strategische Forschungsbereiche und Zentren
- Forschungsschwerpunkt: Gehirn, Hormone, Verhalten - Center for Brain, Behavior and Metabolism (CBBM)
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