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额顶网络功能改变与精神分裂症认知损害的相关性

A study of the relationship between altered frontoparietal network function and cognitive impairment in schizophrenia
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摘要 目的:基于fMRI探讨精神分裂症患者额顶网络中背外侧前额叶(DLPFC)和顶下小叶(IPL)功能改变与认知损害的相关性。方法:于2015年-2020年前瞻性招募在本院就诊的151例精神分裂症患者及年龄、性别、民族和利手相匹配的60例健康对照者。采集每个受试者的静息态fMRI图像和高分辨率T_(1)WI图像,在MATLAB软件中将双侧DLPFC、IPL作为种子点进行局部一致性(Reho)分析。同期由临床医师采用中国修订韦氏成人智力量表(WAIS-RC)评估每例受试者的认知功能,包括数字广度顺背、倒背粗分和数字符号得分。根据认知功能评分将患者分为认知正常组(患者得分低于健康对照组平均得分的0.5个标准差以下即为认知正常)及认知损害组(患者得分低于健康对照组得分的1个标准差以上即为认知损害)。采用Pearson或Spearman相关性分析方法对认知功能评分与ReHo值进行分析。此外,将双侧DLPFC、IPL作为种子点进行有效功能连接分析,并采用曼-惠特尼U检验进行组间比较。结果:对照组的数字顺背粗分与右侧DLPFC的ReHo值呈正相关性(r=0.446,校正后P=0.0012);在左侧IPL的相关性分析中,对照组和认知正常组的数字倒背粗分与ReHo值均呈正相关(r=0.374,校正后P=0.0117;r=0.548,校正后P=0.0372),而认知损害组认知评分与fMRI指标之间均无显著相关性(P>0.05)。有效连接分析结果显示从右侧到左侧DLPFC的有效连接在对照组与认知损害组之间的差异有统计学意义(P<0.05)。结论:DLPFC和IPL的功能改变在精神分裂症患者认知障碍的发病机制中起着重要作用,提示可以将DLPFC和IPL作为无创性神经刺激治疗精神分裂症认知障碍的靶点进行研究,从而有助于探索优化目前的临床治疗策略。 Objective:The purpose of this study was to explore the large-scale mechanisms behind cognitive impairment in schizophrenia patients and explore the relationship between the left dorsolateral prefrontal cortex(DLPFC)and inferior parietal lobule(IPL)function and cognitive impairment in patients with schizophrenia using functional magnetic resonance imaging(fMRI).Methods:From 2015 to 2020,we prospectively recruited 151 patients with schizophrenia and 60 healthy controls who visited our hospital.Resting-state fMRI images and high-resolution T_(1)-weighted images were collected from each subject.Concurrently,clinical physicians assessed the cognitive function of each subject using the Wechsler Adult Intelligence Scale-Revised in China(WAIS-RC),calculating scores for the forward and backward digit span and the digit symbol test.Based on cognitive function scores,patients were categorized into a cognitive normal group(patients scoring below 0.5 standard deviations of the healthy controls were considered cognitively normal)and a cognitive impairment group(patients scoring below 1 standard deviation of the healthy controls were considered to have cognitive impairment).Regional homogeneity(ReHo)based on fMRI was chosen to characterise local resting-state brain functional connectivity,and we used bilateral DLPFC,IPL as seed points for Reho analysis in MATLAB software.Pearson or Spearman correlation analysis methods were employed to analyze the correlation between cognitive function scores and fMRI indicators,specifically the ReHo values.Additionally,effective functional connectivity analysis was conducted using bilateral DLPFC and IPL as seed points,and group comparisons were made using the Mann-Whitney U-test.Results:The study showed a correlation between the digit forward crude scores and the ReHo values of the right DLPFC in healthy controls(r=0.446,P adj=0.0012);in the correlation analysis of the left IPL,there was a positive correlation between the digit backward crude scores and the ReHo values in both healthy controls and cognitively normal patients(r=0.374,P adj=0.0117;r=0.548,P adj=0.0372),while no significant correlation was observed between cognitive impairment group scores and ReHo values(P>0.05).Effective connectivity analysis showed that effective connectivity from the right DLPFC to the left DLPFC differed between healthy controls and cognitively impaired patients(P<0.05).Conclusion:This study suggested that function changes in DLPFC and IPL play an important role in cognitive impairment in schizophrenia.This finding indicates that DLPFC,IPL may be a target for noninvasive neurostimulation for cognitive impairment in schizophrenia,which can help optimize current clinical treatment strategies.
作者 顾悦文 刘晓帆 范靖雯 姜金波 李小飒 李娟娟 印弘 崔龙彪 GU Yue-wen;FAN Jing-wen;JIANG Jin-bo(Department of Psychiatry,Xijing 986 Hospital,Fourth Military Medical University,Xi'an 710054,China)
出处 《放射学实践》 CSCD 北大核心 2024年第8期1007-1013,共7页 Radiologic Practice
基金 国家自然科学基金(82271949) 中国博士后科学基金(2020M683739) 空军军医大学人才扶持“凌云工程”雏鹰计划(2019CYJH) 陕西省自然科学基金青年项目(2022-JQ908)。
关键词 精神分裂症 磁共振成像 认知功能障碍 脑功能网络 Schizophrenia Magnetic resonance imaging Cognition impairment Brain function network
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