首发精神分裂症患者脑灰质和脑网络的磁共振成像研究
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摘要
目的
基于结构磁共振(magnetic resonance imaging, MRI)脑灰质密度的检测,发现精神分裂症脑灰质结构密度减少,但是脑影像表型与临床症状表现型之间的关系仍未明。通过比较有无关系妄想为主要精神症状的首发精神分裂症患者脑灰质密度,将使我们更好的认识关系妄想这种常见临床症状的生物学基础,从而加深我们对精神分裂症生物学机制的理解,并为首发精神分裂症的早期诊断提供科学依据。
方法
按DSM-Ⅳ的精神分裂症诊断标准,入组首发精神病患者44例和年龄、性别及教育水平与之匹配的健康对照25人。对每一位受试者进行韦氏成人智测量表中的常识和数字符号测验评估。采用阳性症状量表(Scale for the Assessment of Positive Symptoms, SAPS)、阴性症状量表(Scale for the Assessment of Negative Symptoms, SANS)及关系妄想半定式访谈量表对患者的精神症状进行评估,并根据关系妄想的评分将患者分为三组：(1)关系妄想组(n=15)：以阳性症状关系妄想为主要临床表现；(2)非关系妄想组(n=14)：以其他阳性症状而不是关系妄想为主要临床表现；(3)阴性症状组(n=15)：以阴性症状为主要临床表现。以基于体素的形态测量法(voxel-based morphometry, VBM)对脑灰质结构MR]图像进行预处理,得到每一个体的灰质密度图像。采用协方差分析,引入年龄、性别、教育水平及颅内总体积为协变量,检测四组间灰质密度存在差异的脑区。然后提取差异脑区的灰质密度绝对值,进行组间的单因素方差分析及采用post hoc检验进行组间两两比较,采用Spearman秩相关以探索脑灰质异常与临床特征之间的相关关系。
结果
四组间脑灰质密度比较的协方差分析发现存在显著差异的脑区位于左,右侧尾状核头、双侧丘脑及左侧小脑后叶(p<0.001, cluster size>200);与非关系妄想组,阴性症状组及健康对照组的受试者相比,关系妄想组患者存在双侧尾状核头灰质密度的显著下降,而其他三组受试者之间的双侧尾状核头灰质密度值无显著性差异；与正常对照相比,患者均存在双侧丘脑和左侧小脑后叶灰质密度下降,而三组患者之间的双侧丘脑和左侧小脑后叶灰质密度无显著性差异；另外,双侧尾状核头灰质密度与关系妄想的严重程度呈显著负相关(r=-0.333,p<0.05；r=-0.383,p<0.05)。
结论
关系妄想为主的精神分裂症患者与其他几组患者及健康对照相比,两侧尾状核头部灰质密度下降并与关系妄想显著负相关,提示两侧尾状核头部灰质密度下降可能是关系妄想形成的神经生物学基础。
目的
基于种子点和独立主成份分析发现静息状态下精神分裂症患者的功能连接增强或减弱的脑区包括皮层到边缘系统,但是由于这两种分析方法的局限性使我们无法了解到全脑的整体的脑功能。本研究使用我们最新发表在分子精神病学(Molencular Psychiatry)的分析方法,构建首发精神分裂症患者静息状态的脑网络内部及脑网络之间的功能连接异常模型,更深入的探讨首发精神分裂症患者脑功能改变的神经生物学机制,寻找精神分裂症可能的神经生物学标记。
方法
入组首发精神分裂症(first-episode schizophrenia, FES)41例和与之年龄、性别和教育水平相互匹配的健康对照(healthy controls,HC)33人。所受试者者均接受静息状态下的功能磁共振(functional MRI, fMRI)扫描。采用(SAPS)和SANS对患者的精神症状进行评估。使用MATLAB7.8.SPM8和Data Processing Assistant for Resting-State fMRI (DPARSF)进行fMRI数据预处理。用网络探索算法(community discovery algorithm)对33个健康受试者的脑功能网络进行探索与构建以获取脑功能网络的结构模板,并以此做为FES组的脑功能网络模板。以脑解剖图谱为模板(共有90个ROI)分别提取每一位受试者的90个ROI的时间序列,进行功能连接分析(Pearson相关分析,p<0.01)。采用偏相关检验(p<0.01)以消除任两个ROI之间的假阳性相关。计算脑区之间的功能连接与疾病之间的关联强度即优势比(odds ratio, OR)以确定与疾病存在显著关联的功能连接,并比较两组之间的功能连接差异。
结果
(1)采用网络探索算法(community discovery algorithm)构建的脑功能网络模型有默认网络、注意网络、视觉识别网络、听觉网络、感觉运动网络及皮质下网络。
(2)与HC相比,FES患者默认网络内部的连接减弱；默认网络与注意网络之间的功能连接异常增强与减弱并存；默认网络与视觉识别网络、听觉网络之间的功能连接显著增强而与皮质下网络连接减弱。
(3)FES患者的其它脑网络内部及之间的连接模式异常表现为：FES患者的听觉网络、视觉识别网络内部的连接异常增强与减弱并存,而皮质下网络的连接明显减弱；FES患者注意网络与视觉网络之间的连接显著减弱。
(4)FES患者的左右大脑半球存在显著的功能失连接。
结论
本研究发现首发精神分裂症患者静息态脑网络功能连接模式存在明显异常,异常的连接模式涉及整个脑功能网络。结果提示首发精神分裂症患者静息态脑网络功能连接模式可能是精神症状包括幻觉、妄想、思维障碍形式障碍、动作与行为障碍等及“认知辨距不良”的神经病理基础。
Objective
Delusions of reference (DOR) are one of the most common psychotic symptoms, which are closely linked with dopamine activities theoretically. This study using magnetic resonance imaging (MRI) aims to explore their neuroanatomical substrates, in particular in the basal ganglia.
Methods
A total of44first-episode psychosis patients and25well-matched healthy controls were recruited. Patients were divided into three groups according to their clinical profile:(1) DOR group (n=15) with DOR as chief positive symptom,(2) non-DOR group (n=14) with positive symptoms other than DOR, and (3) negative group (n=15) with minimal positive symptoms. All participants underwent a structural magnetic resonance imaging scan of the brain. Voxel-based morphometry analysis was used to detect group differences in gray matter density. The relationship between DOR and structural anomalies was explored using Spearman's correlation.
Results
Significant group difference was observed in left and right caudate head, bilateral thalamus and left cerebellum. Post-hoc analysis showed that DOR patients had lower gray matter density in the caudate head bilaterally, which showed no difference among the other three groups. Gray matter density in the left and right caudate head was negatively correlated with DOR severity rho=-0.333and-0.383, both p<0.05). All patients exhibited reduced gray matter density bilaterally in the thalamus and left cerebellar posterior lobe compared with controls.
Conclusion
Gray matter deficit in the caudate head is specifically observed in first-episode psychosis patients with DOR and is related to the severity of the symptom. Structural anomalies in the caudate may be related to the experience of DOR in psychosis.
Objective
Abnormal Functional connectivity including corticol-subcortical brain regions in schizophrenia have been detected by Seed-based analysis and independent component analysis approach. However, in consideration of limitations, more holistic and objective approach is needed. A new holistic approach was used to construct the abnormal functional connectivity model within and between brain networks in patients of first episode schizophrenia and seek to provide new clues and evidences for the understanding of the pathology mechanism and biological makers of schizophrenia.
Methods
Forty-one patients with first-episode schizophrenia (FES) and33well-matched healthy controls (HC) were recruited. All participants underwent a resting state functional magnetic resonance imaging (fMRI) scan of the brain. Psychotic symptoms were assessed by SAPS and SANS. fMRI data preprocessing was conducted by SPM8(Statistical Parametric Mapping) and DPARSF (Data Processing Assistant for resting-state fMRI). Community discovery algorithm was used to explore and construct functional brain networks in healthy control subjects. A canonical template of connectivity in90different brain regions was constructed from healthy control subjects and this identified a six community structure with each network corresponding to a different functional system. An automated anatomical labeling atlas was used to parcellate the brain into90regions of interest (ROIs). The time series were extracted in each ROI by averaging the signals of all voxels within that region. Pearson correlation coefficients between all pairs of ROIs were first calculated (P-value<0.01). Significant correlations were detected with a90×90correlation matrix was obtained for each subject and then tested by partial correlation analysis (P-value<0.01).Odds ratio which represents the strength of association between functional connectivity and the disease was calculated and the differences of functional connectivities were compared between groups.
Results
(1) Six different brain functional networks were constructed using a community discovery algorithm. That is default mode network, attention network, auditory network, visual recognition network, the sensory-motor areas and subcortical network.
(2) Compared with HC, patients with FES showed obviously decreased functional connectivity within default mode network, significantly decreased and increased functional connectivity between default mode network and attention network, significantly increased functional connectivity between default mode network and visual recognition network and auditory network, and decreased functional connectivity between default mode network and subcortical network.
(3) Other abnormal functional connectivities within single brain network and between different brain networks were also detected in patients with FES. The abnormal functional connectivitiy model involved significantly decreased and increased functional connectivity within auditory network and visual recognition network, and significantly decreased functional connectivity within subcortical network. In addition, obviously decreased functional connectivity was also detected between attention network and visual recognition network.
(4) Functional dysconnectivity of the left and right Brain's Hemispheres existed in patients with FES.
Conclusion
Abnormal Functional connectivities involved all the different brain networks were observed in patients with FES. This may represent the pathophysiology underlying psychotic symptoms including hallucinations, delusions, positive formal thought disorder, bizarre behavior and congnitive dymentia.
基于结构磁共振(magnetic resonance imaging, MRI)脑灰质密度的检测,发现精神分裂症脑灰质结构密度减少,但是脑影像表型与临床症状表现型之间的关系仍未明。通过比较有无关系妄想为主要精神症状的首发精神分裂症患者脑灰质密度,将使我们更好的认识关系妄想这种常见临床症状的生物学基础,从而加深我们对精神分裂症生物学机制的理解,并为首发精神分裂症的早期诊断提供科学依据。
方法
按DSM-Ⅳ的精神分裂症诊断标准,入组首发精神病患者44例和年龄、性别及教育水平与之匹配的健康对照25人。对每一位受试者进行韦氏成人智测量表中的常识和数字符号测验评估。采用阳性症状量表(Scale for the Assessment of Positive Symptoms, SAPS)、阴性症状量表(Scale for the Assessment of Negative Symptoms, SANS)及关系妄想半定式访谈量表对患者的精神症状进行评估,并根据关系妄想的评分将患者分为三组：(1)关系妄想组(n=15)：以阳性症状关系妄想为主要临床表现；(2)非关系妄想组(n=14)：以其他阳性症状而不是关系妄想为主要临床表现；(3)阴性症状组(n=15)：以阴性症状为主要临床表现。以基于体素的形态测量法(voxel-based morphometry, VBM)对脑灰质结构MR]图像进行预处理,得到每一个体的灰质密度图像。采用协方差分析,引入年龄、性别、教育水平及颅内总体积为协变量,检测四组间灰质密度存在差异的脑区。然后提取差异脑区的灰质密度绝对值,进行组间的单因素方差分析及采用post hoc检验进行组间两两比较,采用Spearman秩相关以探索脑灰质异常与临床特征之间的相关关系。
结果
四组间脑灰质密度比较的协方差分析发现存在显著差异的脑区位于左,右侧尾状核头、双侧丘脑及左侧小脑后叶(p<0.001, cluster size>200);与非关系妄想组,阴性症状组及健康对照组的受试者相比,关系妄想组患者存在双侧尾状核头灰质密度的显著下降,而其他三组受试者之间的双侧尾状核头灰质密度值无显著性差异；与正常对照相比,患者均存在双侧丘脑和左侧小脑后叶灰质密度下降,而三组患者之间的双侧丘脑和左侧小脑后叶灰质密度无显著性差异；另外,双侧尾状核头灰质密度与关系妄想的严重程度呈显著负相关(r=-0.333,p<0.05；r=-0.383,p<0.05)。
结论
关系妄想为主的精神分裂症患者与其他几组患者及健康对照相比,两侧尾状核头部灰质密度下降并与关系妄想显著负相关,提示两侧尾状核头部灰质密度下降可能是关系妄想形成的神经生物学基础。
目的
基于种子点和独立主成份分析发现静息状态下精神分裂症患者的功能连接增强或减弱的脑区包括皮层到边缘系统,但是由于这两种分析方法的局限性使我们无法了解到全脑的整体的脑功能。本研究使用我们最新发表在分子精神病学(Molencular Psychiatry)的分析方法,构建首发精神分裂症患者静息状态的脑网络内部及脑网络之间的功能连接异常模型,更深入的探讨首发精神分裂症患者脑功能改变的神经生物学机制,寻找精神分裂症可能的神经生物学标记。
方法
入组首发精神分裂症(first-episode schizophrenia, FES)41例和与之年龄、性别和教育水平相互匹配的健康对照(healthy controls,HC)33人。所受试者者均接受静息状态下的功能磁共振(functional MRI, fMRI)扫描。采用(SAPS)和SANS对患者的精神症状进行评估。使用MATLAB7.8.SPM8和Data Processing Assistant for Resting-State fMRI (DPARSF)进行fMRI数据预处理。用网络探索算法(community discovery algorithm)对33个健康受试者的脑功能网络进行探索与构建以获取脑功能网络的结构模板,并以此做为FES组的脑功能网络模板。以脑解剖图谱为模板(共有90个ROI)分别提取每一位受试者的90个ROI的时间序列,进行功能连接分析(Pearson相关分析,p<0.01)。采用偏相关检验(p<0.01)以消除任两个ROI之间的假阳性相关。计算脑区之间的功能连接与疾病之间的关联强度即优势比(odds ratio, OR)以确定与疾病存在显著关联的功能连接,并比较两组之间的功能连接差异。
结果
(1)采用网络探索算法(community discovery algorithm)构建的脑功能网络模型有默认网络、注意网络、视觉识别网络、听觉网络、感觉运动网络及皮质下网络。
(2)与HC相比,FES患者默认网络内部的连接减弱；默认网络与注意网络之间的功能连接异常增强与减弱并存；默认网络与视觉识别网络、听觉网络之间的功能连接显著增强而与皮质下网络连接减弱。
(3)FES患者的其它脑网络内部及之间的连接模式异常表现为：FES患者的听觉网络、视觉识别网络内部的连接异常增强与减弱并存,而皮质下网络的连接明显减弱；FES患者注意网络与视觉网络之间的连接显著减弱。
(4)FES患者的左右大脑半球存在显著的功能失连接。
结论
本研究发现首发精神分裂症患者静息态脑网络功能连接模式存在明显异常,异常的连接模式涉及整个脑功能网络。结果提示首发精神分裂症患者静息态脑网络功能连接模式可能是精神症状包括幻觉、妄想、思维障碍形式障碍、动作与行为障碍等及“认知辨距不良”的神经病理基础。
Objective
Delusions of reference (DOR) are one of the most common psychotic symptoms, which are closely linked with dopamine activities theoretically. This study using magnetic resonance imaging (MRI) aims to explore their neuroanatomical substrates, in particular in the basal ganglia.
Methods
A total of44first-episode psychosis patients and25well-matched healthy controls were recruited. Patients were divided into three groups according to their clinical profile:(1) DOR group (n=15) with DOR as chief positive symptom,(2) non-DOR group (n=14) with positive symptoms other than DOR, and (3) negative group (n=15) with minimal positive symptoms. All participants underwent a structural magnetic resonance imaging scan of the brain. Voxel-based morphometry analysis was used to detect group differences in gray matter density. The relationship between DOR and structural anomalies was explored using Spearman's correlation.
Results
Significant group difference was observed in left and right caudate head, bilateral thalamus and left cerebellum. Post-hoc analysis showed that DOR patients had lower gray matter density in the caudate head bilaterally, which showed no difference among the other three groups. Gray matter density in the left and right caudate head was negatively correlated with DOR severity rho=-0.333and-0.383, both p<0.05). All patients exhibited reduced gray matter density bilaterally in the thalamus and left cerebellar posterior lobe compared with controls.
Conclusion
Gray matter deficit in the caudate head is specifically observed in first-episode psychosis patients with DOR and is related to the severity of the symptom. Structural anomalies in the caudate may be related to the experience of DOR in psychosis.
Objective
Abnormal Functional connectivity including corticol-subcortical brain regions in schizophrenia have been detected by Seed-based analysis and independent component analysis approach. However, in consideration of limitations, more holistic and objective approach is needed. A new holistic approach was used to construct the abnormal functional connectivity model within and between brain networks in patients of first episode schizophrenia and seek to provide new clues and evidences for the understanding of the pathology mechanism and biological makers of schizophrenia.
Methods
Forty-one patients with first-episode schizophrenia (FES) and33well-matched healthy controls (HC) were recruited. All participants underwent a resting state functional magnetic resonance imaging (fMRI) scan of the brain. Psychotic symptoms were assessed by SAPS and SANS. fMRI data preprocessing was conducted by SPM8(Statistical Parametric Mapping) and DPARSF (Data Processing Assistant for resting-state fMRI). Community discovery algorithm was used to explore and construct functional brain networks in healthy control subjects. A canonical template of connectivity in90different brain regions was constructed from healthy control subjects and this identified a six community structure with each network corresponding to a different functional system. An automated anatomical labeling atlas was used to parcellate the brain into90regions of interest (ROIs). The time series were extracted in each ROI by averaging the signals of all voxels within that region. Pearson correlation coefficients between all pairs of ROIs were first calculated (P-value<0.01). Significant correlations were detected with a90×90correlation matrix was obtained for each subject and then tested by partial correlation analysis (P-value<0.01).Odds ratio which represents the strength of association between functional connectivity and the disease was calculated and the differences of functional connectivities were compared between groups.
Results
(1) Six different brain functional networks were constructed using a community discovery algorithm. That is default mode network, attention network, auditory network, visual recognition network, the sensory-motor areas and subcortical network.
(2) Compared with HC, patients with FES showed obviously decreased functional connectivity within default mode network, significantly decreased and increased functional connectivity between default mode network and attention network, significantly increased functional connectivity between default mode network and visual recognition network and auditory network, and decreased functional connectivity between default mode network and subcortical network.
(3) Other abnormal functional connectivities within single brain network and between different brain networks were also detected in patients with FES. The abnormal functional connectivitiy model involved significantly decreased and increased functional connectivity within auditory network and visual recognition network, and significantly decreased functional connectivity within subcortical network. In addition, obviously decreased functional connectivity was also detected between attention network and visual recognition network.
(4) Functional dysconnectivity of the left and right Brain's Hemispheres existed in patients with FES.
Conclusion
Abnormal Functional connectivities involved all the different brain networks were observed in patients with FES. This may represent the pathophysiology underlying psychotic symptoms including hallucinations, delusions, positive formal thought disorder, bizarre behavior and congnitive dymentia.
引文
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