Shared Transcriptional Signatures in Major Depressive Disorder and Mouse Chronic Stress Models

重度抑郁症和鼠慢性应激模型中共同的转录特征

阅读:1

Abstract

BACKGROUND: Most of our knowledge of the biological basis of major depressive disorder (MDD) is derived from studies of chronic stress models in rodents. While these models capture certain aspects of the behavioral and neuroendocrine features of MDD, the extent to which they reproduce the molecular pathology of the human syndrome remains unknown. METHODS: We systematically compared transcriptional signatures in two brain regions implicated in depression-medial prefrontal cortex and nucleus accumbens-of humans with MDD and of 3 chronic stress models in mice: chronic variable stress, adult social isolation, and chronic social defeat stress. We used differential expression analysis combined with weighted gene coexpression network analysis to create interspecies gene networks and assess the capacity of each stress paradigm to recapitulate the transcriptional organization of gene networks in human MDD. RESULTS: Our results show significant overlap between transcriptional alterations in medial prefrontal cortex and nucleus accumbens in human MDD and the 3 mouse chronic stress models, with each of the chronic stress paradigms capturing distinct aspects of MDD abnormalities. Chronic variable stress and adult social isolation better reproduce differentially expressed genes, while chronic social defeat stress and adult social isolation better reproduce gene networks characteristic of human MDD. We also identified several gene networks and their constituent genes that are most significantly associated with human MDD and mouse stress models. CONCLUSIONS: This study demonstrates the ability of 3 chronic stress models in mice to recapitulate distinct aspects of the broad molecular pathology of human MDD, with no one mouse model apparently better than another.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。