通过对死后人类大脑的转录组学分析鉴定神经新生标志物。

IF 4.1 Q2 GERIATRICS & GERONTOLOGY
Shiva Kazempour Dehkordi, Sogand Sajedi, Amirreza Heshmat, Miranda E Orr, Habil Zare
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引用次数: 0

摘要

神经元衰老(即神经新生)是衰老和神经退行性变的重要标志,但由于缺乏可靠的标志物,它在人脑中的特征仍然很差。本研究旨在根据死后人类前额皮质的单核转录组数据鉴定神经标记。采用特征基因方法,我们整合了三个基因面板:(a) SenMayo, (b)典型衰老途径(CSP)和(c)衰老启动途径(SIP),以识别神经特征。我们发现成对标记优于单个标记;例如,通过在决策树中结合CDKN2D和ETS2,在区分衰老神经元(即神经新生)方面实现了99%的高精度和100%的完美特异性。差异表达分析确定了神经新生中过表达的324个基因。这些基因显示出与重要的神经退行性相关通路的显著关联,包括阿尔茨海默病、帕金森病和亨廷顿病。有趣的是,这些过度表达的基因中有几个与线粒体功能障碍和细胞骨架失调有关。这些发现为神经再生的复杂性提供了有价值的见解,强调需要进一步探索组织学上可行的标记物并在更广泛的数据集中进行验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of markers for neurescence through transcriptomic profiling of postmortem human brains.

Neuronal senescence (i.e., neurescence) is an important hallmark of aging and neurodegeneration, but it remains poorly characterized in the human brain due to the lack of reliable markers. This study aimed to identify neurescence markers based on single-nucleus transcriptome data from postmortem human prefrontal cortex. Using an eigengene approach, we integrated three gene panels: (a) SenMayo, (b) canonical senescence pathway (CSP), and (c) senescence initiating pathway (SIP), to identify neurescence signatures. We found that paired markers outperform single markers; for instance, by combining CDKN2D and ETS2 in a decision tree, a high accuracy of 99% and perfect specificity (100%) were achieved in distinguishing senescent neurons (i.e, neurescent). Differential expression analyses identified 324 genes that are overexpressed in neurescent. These genes showed significant associations with important neurodegeneration-related pathways, including Alzheimer's disease, Parkinson's disease, and Huntington's disease. Interestingly, several of these overexpressed genes are linked to mitochondrial dysfunction and cytoskeletal dysregulation. These findings provide valuable insights into the complexities of neurescence, emphasizing the need for further exploration of histologically viable markers and validation in broader datasets.

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CiteScore
8.90
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