Dehkordi Shiva Kazempour, Sajedi Sogand, Heshmat Amirreza, Orr Miranda E, Zare Habil
The University of Texas Health Science Center at San Antonio.
The University of Texas MD Anderson Cancer Center.
Res Sq. 2025 Apr 9:rs.3.rs-5903682. doi: 10.21203/rs.3.rs-5903682/v1.
Neuronal senescence (i.e., neurescent) 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 neurescent 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 neurescent signatures. We found that paired markers outperform single markers; for instance, by combining and in a decision tree, a high accuracy of 99% and perfect specificity (100%) were achieved in distinguishing 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 neurescent, emphasizing the need for further exploration of histologically viable markers and validation in broader datasets.
神经元衰老（即神经衰老）是衰老和神经退行性变的一个重要标志，但由于缺乏可靠的标志物，在人类大脑中其特征仍不清楚。本研究旨在基于死后人类前额叶皮层的单核转录组数据鉴定神经衰老标志物。使用特征基因方法，我们整合了三个基因面板：a）SenMayo，b）经典衰老途径（CSP），以及c）衰老起始途径（SIP），以鉴定神经衰老特征。我们发现配对标志物优于单个标志物；例如，通过在决策树中组合 和 ，在区分神经衰老方面实现了99%的高准确率和完美的特异性（100%）。差异表达分析确定了324个在神经衰老中过度表达的基因。这些基因与包括阿尔茨海默病、帕金森病和亨廷顿病在内的重要神经退行性变相关途径显示出显著关联。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。这些发现为神经衰老的复杂性提供了有价值的见解，强调了进一步探索组织学上可行的标志物并在更广泛的数据集中进行验证的必要性。
