A study on the early response to antipsychotic medication in schizophrenia based on modular brain networks
10.3969/j.issn.1002-0152.2025.10.005
- VernacularTitle:基于模块化脑网络的精神分裂症抗精神病药物早期治疗应答研究
- Author:
Wenming LIU
1
;
Chen WANG
;
Xiancang MA
Author Information
1. 西安交通大学第一附属医院精神心理科(西安 710061);空军军医大学第一附属医院心身科
- Publication Type:Journal Article
- Keywords:
Schizophrenia;
Magnetic resonance imaging;
Gray matter;
Antipsychotic agents;
Neuroimaging;
Module;
Topological attribute;
Gray matter nucleus network;
Default network;
Sensorimotor network
- From:
Chinese Journal of Nervous and Mental Diseases
2025;51(10):608-614
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the differences in the topological attributes of the baseline state functional network module between responders and non-responders to pharmacological treatment in schizophrenia patients.Methods Patients with first-episode untreated schizophrenia were included.The therapeutic effect was evaluated 4 weeks after receiving standardized clinical treatment based on the percentage change of the positive and negative syndrome scale(PANSS)score before and after treatment.The patients were divided into the response group(n=45)and the non-response group(n=32).The modular topological properties of the brain functional network were calculated using resting-state functional magnetic resonance imaging(rs-fMRI)technology.The differences in functional connectivity between the treatment response group and the non-response group were then compared.The correlation between the functional connection of the patient's network module and the PANSS score was analyzed.Results Compared to the non-responder group,the responder group exhibited increased modularity and a higher average node participation coefficient.Moreover,the default network module exhibited a decreased separation index,whereas an increase was observed in the sensorimotor module separation index.Additionally,intra-modular connectivity was reduced within the visual network,sensorimotor module and subcortical nuclei module.The connections among the gray matter nucleus-visual module,gray matter nucleus-marginal module,gray matter nucleus-default network,gray matter nucleus-sensorimotor module and sensorimotor default network modules were decreased(FDR correction,P<0.05).The interconnections between gray matter nuclei-default network(r=0.42,P<0.01)and sensorimotor-default network modules(r=0.31,P=0.04)in the response group were positively correlated with the positive symptom scores,respectively.Receiver operating characteristic(ROC)curve analysis showed that the modular connection of functional networks had good classification prediction efficacy(AUC=0.858,95%CI:0.759-0.927).Conclusion The modular connections among the gray matter nucleus network,default network and sensorimotor network may provide neuroimaging evidence for the prediction of the efficacy of drug treatment for schizophrenia.
