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神经组织的共表达网络分析揭示了精神分裂症中发育过程的紊乱。

Coexpression network analysis of neural tissue reveals perturbations in developmental processes in schizophrenia.

机构信息

Scripps Translational Science Institute, La Jolla, California 92037, USA.

出版信息

Genome Res. 2010 Apr;20(4):403-12. doi: 10.1101/gr.101956.109. Epub 2010 Mar 2.

Abstract

We performed integrated gene coexpression network analysis on two large microarray-based brain gene expression data sets generated from the prefrontal cortex obtained post-mortem from 101 subjects, 47 subjects with schizophrenia and 54 normal control subjects, ranging in age from 19 to 81 years. Twenty-eight modules of coexpressed genes with functional interpretations were detected in both normal subjects and those with schizophrenia. Significant overlap of "case" and "control" module composition was observed, indicating that extensive differences in underlying molecular connectivity are not likely driving pathology in schizophrenia. Modules of coexpressed genes were characterized according to disease association, cell type specificity, and the effects of aging. We find that genes with altered expression in schizophrenia clustered into distinct coexpression networks and that these were associated primarily with neurons. We further identified a robust effect of age on gene expression modules that differentiates normal subjects from those with schizophrenia. In particular, we report that normal age-related decreases in genes related to central nervous system developmental processes, including neurite outgrowth, neuronal differentiation, and dopamine-related cellular signaling, do not occur in subjects with schizophrenia during the aging process. Extrapolating these findings to earlier stages of development supports the concept that schizophrenia pathogenesis begins early in life and is associated with a failure of normal decreases in developmental-related gene expression. These findings provide a novel mechanism for the "developmental" hypothesis of schizophrenia on a molecular level.

摘要

我们对两个大型的基于微阵列的大脑基因表达数据集进行了综合基因共表达网络分析,这些数据集来自 101 名受试者的前额叶皮层,其中 47 名患有精神分裂症,54 名是正常对照组,年龄从 19 岁到 81 岁不等。在正常受试者和精神分裂症患者中都检测到了 28 个具有功能解释的共表达基因模块。观察到“病例”和“对照”模块组成的显著重叠,表明在精神分裂症中,潜在的分子连接差异不大。根据疾病相关性、细胞类型特异性和衰老的影响对共表达基因模块进行了特征描述。我们发现,在精神分裂症中表达改变的基因聚类到不同的共表达网络中,这些网络主要与神经元有关。我们进一步确定了年龄对基因表达模块的显著影响,这可以将正常受试者与精神分裂症患者区分开来。特别是,我们报告说,与中枢神经系统发育过程相关的基因(包括神经突生长、神经元分化和多巴胺相关细胞信号传导)的正常年龄相关性降低在精神分裂症患者中不会发生衰老过程中。将这些发现推断到发育的早期阶段,支持了精神分裂症发病机制早在生命早期开始的概念,并且与正常发育相关基因表达降低的失败有关。这些发现为精神分裂症的“发育”假说提供了一个分子水平上的新机制。

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