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氯氮平或利培酮治疗与未治疗慢性精神分裂症患者的脑白质结构网络特征。

Characteristics of White Matter Structural Networks in Chronic Schizophrenia Treated With Clozapine or Risperidone and Those Never Treated.

机构信息

Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.

Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, China.

出版信息

Int J Neuropsychopharmacol. 2020 Dec 29;23(12):799-810. doi: 10.1093/ijnp/pyaa061.

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.

摘要

背景

尽管抗精神病药物治疗有其益处,但人们主要关注的是它可能对大脑结构和功能产生的影响。本研究旨在探讨慢性未经治疗的精神分裂症患者以及接受氯氮平或利培酮单药治疗的患者的白质结构网络特征,及其与认知功能的潜在关联。

方法

对一个独特的样本进行了弥散张量成像,该样本包括 34 名接受抗精神病药物单药治疗超过 5 年的精神分裂症患者(17 名接受氯氮平治疗,17 名接受利培酮治疗)、17 名未经治疗且病程超过 5 年的精神分裂症患者和 27 名健康对照参与者。采用图论和基于网络的统计方法。

结果

我们观察到白质结构网络的组织紊乱以及精神分裂症组的节点和连接特征降低,主要涉及丘脑、前额叶和枕叶区域。与氯氮平治疗组和未治疗组相比,利培酮治疗组患者的节点和连接特征变化相对较轻。改变的全局网络测量值与认知表现水平显著相关。基于网络的统计反映的结构连接介导了氯氮平治疗组和利培酮治疗组患者认知表现水平的差异。

局限性

这些结果受到缺乏随机分配到不同类型抗精神病药物治疗的限制。

结论

这些发现深入了解了慢性精神分裂症患者(无论是接受治疗还是未接受治疗)的白质结构网络缺陷,并表明支持认知功能的白质结构网络可能受益于抗精神病药物治疗,尤其是接受利培酮治疗的患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d609/7770521/865ba7d4605d/pyaa061_fig1.jpg

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