Abstract：
BACKGROUND: Depressive symptoms are a common concomitant of cerebral small vessel disease (CSVD), of which pathogenesis requires more study. White matter microstructural abnormalities and proteomic alternation have been widely reported regarding depression in the elderly with CSVD. Exploring the relationship between cerebral white matter microstructural alterations and serum proteins may complete the explanation of molecular mechanisms for the findings from neuroimaging research of CSVD combined with depressive symptoms.
METHODS: An untargeted proteomics approach based on mass spectrometry was used to obtain serum proteomic profiles, which were clustered into co-expression protein modules. White matter microstructural integrity was measured using the FMRIB Software Library (FSL) and MATLAB to analyze diffusion tensor imaging (DTI) data and calculate the differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) for 50 regions of interest (ROI). Integrating the proteome with the DTI results, weighted gene co-expression analysis (WGCNA) was used to identify protein modules related to white matter microstructural alterations, and the proteins of the corresponding modules were analyzed for functional enrichment through bioinformatics techniques.
RESULTS: DTI measurements were analCerebral small vessel disease (CSVD); Depression; Diffusion tensor imaging (DTI); Proteomics; Inflammationyzed between individuals with CSVD and depressive symptoms (CSVD+D) (n = 24) and those without depressive symptoms (CSVD-D) (n = 35). Results showed an overall increase in MD, AD, and RD within the left hemisphere of the CSVD+D group, suggesting widespread loss of white matter integrity and axonal demyelination, including left superior longitudinal fasciculus (SLF), left posterior corona radiata (PCR) and right external capsule (EC). We identified two protein modules associated with DTI diffusivity, and functional enrichment analyses revealed that complement and coagulation cascades and immune responses participate in the alternation of white matter microstructure in the CSVD+D group.
CONCLUSIONS: The results suggested immune- and inflammation-related mechanism was associated with white matter microstructure changes in CSVD with depressive symptoms.
METHODS: An untargeted proteomics approach based on mass spectrometry was used to obtain serum proteomic profiles, which were clustered into co-expression protein modules. White matter microstructural integrity was measured using the FMRIB Software Library (FSL) and MATLAB to analyze diffusion tensor imaging (DTI) data and calculate the differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) for 50 regions of interest (ROI). Integrating the proteome with the DTI results, weighted gene co-expression analysis (WGCNA) was used to identify protein modules related to white matter microstructural alterations, and the proteins of the corresponding modules were analyzed for functional enrichment through bioinformatics techniques.
RESULTS: DTI measurements were analCerebral small vessel disease (CSVD); Depression; Diffusion tensor imaging (DTI); Proteomics; Inflammationyzed between individuals with CSVD and depressive symptoms (CSVD+D) (n = 24) and those without depressive symptoms (CSVD-D) (n = 35). Results showed an overall increase in MD, AD, and RD within the left hemisphere of the CSVD+D group, suggesting widespread loss of white matter integrity and axonal demyelination, including left superior longitudinal fasciculus (SLF), left posterior corona radiata (PCR) and right external capsule (EC). We identified two protein modules associated with DTI diffusivity, and functional enrichment analyses revealed that complement and coagulation cascades and immune responses participate in the alternation of white matter microstructure in the CSVD+D group.
CONCLUSIONS: The results suggested immune- and inflammation-related mechanism was associated with white matter microstructure changes in CSVD with depressive symptoms.
摘要：
背景：抑郁症状是脑小血管疾病（CSVD）的常见伴随症状，其中的发病机制需要更多的研究。白质微结构异常和蛋白质组改变已被广泛报道与CSVD老年抑郁症有关。探索脑白质微结构改变与血清蛋白之间的关系可能为CSVD合并抑郁症状的神经影像学研究发现的分子机制提供解释。
方法：使用基于质谱的非靶向蛋白质组学方法来获得血清蛋白质组学图谱，它们被聚集到共表达蛋白模块中。使用FMRIB软件库（FSL）和MATLAB测量白质微结构完整性，以分析扩散张量成像（DTI）数据并计算分数各向异性（FA）的差异，平均扩散率（MD），轴向扩散率（AD），和50个感兴趣区域(ROI)的径向扩散率(RD)。将蛋白质组与DTI结果整合，加权基因共表达分析（WGCNA）用于鉴定与白质微结构改变相关的蛋白质模块，并通过生物信息学技术对相应模块的蛋白质进行功能富集分析。
结果：DTI测量结果为脑小血管病（CSVD）；抑郁症；扩散张量成像（DTI）；蛋白质组学；在患有CSVD和抑郁症状（CSVDD）（n=24）和没有抑郁症状（CSVD-D）（n=35）的个体之间发生炎症。结果显示MD总体增加，AD,CSVD+D组左半球的RD，提示白质完整性和轴突脱髓鞘的广泛丧失，包括左上纵束(SLF)，左后冠辐射（PCR）和右外囊（EC）。我们确定了两个与DTI扩散相关的蛋白质模块，功能富集分析表明，补体和凝血级联反应以及免疫反应参与了CSVDD组白质微观结构的改变。
结论：结果表明免疫和炎症相关机制与伴抑郁症状的CSVD脑白质微结构改变有关。
方法：使用基于质谱的非靶向蛋白质组学方法来获得血清蛋白质组学图谱，它们被聚集到共表达蛋白模块中。使用FMRIB软件库（FSL）和MATLAB测量白质微结构完整性，以分析扩散张量成像（DTI）数据并计算分数各向异性（FA）的差异，平均扩散率（MD），轴向扩散率（AD），和50个感兴趣区域(ROI)的径向扩散率(RD)。将蛋白质组与DTI结果整合，加权基因共表达分析（WGCNA）用于鉴定与白质微结构改变相关的蛋白质模块，并通过生物信息学技术对相应模块的蛋白质进行功能富集分析。
结果：DTI测量结果为脑小血管病（CSVD）；抑郁症；扩散张量成像（DTI）；蛋白质组学；在患有CSVD和抑郁症状（CSVDD）（n=24）和没有抑郁症状（CSVD-D）（n=35）的个体之间发生炎症。结果显示MD总体增加，AD,CSVD+D组左半球的RD，提示白质完整性和轴突脱髓鞘的广泛丧失，包括左上纵束(SLF)，左后冠辐射（PCR）和右外囊（EC）。我们确定了两个与DTI扩散相关的蛋白质模块，功能富集分析表明，补体和凝血级联反应以及免疫反应参与了CSVDD组白质微观结构的改变。
结论：结果表明免疫和炎症相关机制与伴抑郁症状的CSVD脑白质微结构改变有关。
