美国艾伦脑科学研究所曾红葵等研究人员，合作揭示了小鼠大脑健康衰老的细胞类型特异性转录组特征。该研究于2025年1月1日发表于国际一流学术期刊《自然》。

研究人员呈现了一份全面的单细胞RNA测序数据集，包含约120万个高质量的小鼠大脑细胞转录组数据，涵盖了来自年轻成年小鼠和衰老小鼠的不同性别样本，并包括前脑、中脑和后脑的多个区域。对所有细胞进行高分辨率聚类分析后，研究人员识别出了847个细胞簇，并揭示出至少14个与年龄相关的簇，这些簇大多属于胶质细胞类型。

在更广泛的细胞子类和超级类型层次上，研究人员发现了与年龄相关的基因表达特征，并提供了2449个独特的差异表达基因（年龄相关差异表达基因，age-DE gene）列表，涵盖了多种神经元和非神经元细胞类型。

尽管大多数年龄相关差异表达基因在特定细胞类型中是独特的，但研究人员观察到不同细胞类型之间普遍存在衰老的共性特征，包括许多神经元类型、主要星形胶质细胞类型和成熟少突胶质细胞中，涉及神经元结构和功能的基因表达降低，而免疫功能、抗原呈递、炎症和细胞运动性相关基因在免疫细胞类型和一些血管细胞类型中表达增加。

最后，研究人员观察到，某些对衰老最敏感的细胞类型集中在下丘脑的第三脑室周围，包括伸长细胞、室管膜细胞以及弓状核、背内侧核和旁丘脑核中的某些神经元类型，这些细胞类型表达与能量稳态相关的基因。这些细胞类型表现出神经功能的下降和免疫反应的增加。

研究结果表明，下丘脑的第三脑室可能是小鼠大脑衰老的一个中心。总体而言，这项研究系统性地描绘了与正常衰老相关的脑部细胞类型特异性转录组变化的动态景观，为衰老过程中功能变化的研究以及衰老与疾病之间相互作用的研究奠定了基础。

据了解，生物学上的衰老可以定义为分子和细胞功能各个方面逐渐失去稳态的过程。哺乳动物大脑由成千上万种不同的细胞类型组成，这些细胞类型对衰老的敏感性和耐受性可能有所不同。

附：英文原文

Title: Brain-wide cell-type-specific transcriptomic signatures of healthy ageing in mice

Author: Jin, Kelly, Yao, Zizhen, van Velthoven, Cindy T. J., Kaplan, Eitan S., Glattfelder, Katie, Barlow, Samuel T., Boyer, Gabriella, Carey, Daniel, Casper, Tamara, Chakka, Anish Bhaswanth, Chakrabarty, Rushil, Clark, Michael, Departee, Max, Desierto, Marie, Gary, Amanda, Gloe, Jessica, Goldy, Jeff, Guilford, Nathan, Guzman, Junitta, Hirschstein, Daniel, Lee, Changkyu, Liang, Elizabeth, Pham, Trangthanh, Reding, Melissa, Ronellenfitch, Kara, Ruiz, Augustin, Sevigny, Josh, Shapovalova, Nadiya, Shulga, Lyudmila, Sulc, Josef, Torkelson, Amy, Tung, Herman, Levi, Boaz, Sunkin, Susan M., Dee, Nick, Esposito, Luke, Smith, Kimberly A., Tasic, Bosiljka, Zeng, Hongkui

Issue&Volume: 2025-01-01

Abstract: Biological ageing can be defined as a gradual loss of homeostasis across various aspects of molecular and cellular function1,2. Mammalian brains consist of thousands of cell types3, which may be differentially susceptible or resilient to ageing. Here we present a comprehensive single-cell RNA sequencing dataset containing roughly 1.2million high-quality single-cell transcriptomes of brain cells from young adult and aged mice of both sexes, from regions spanning the forebrain, midbrain and hindbrain. High-resolution clustering of all cells results in 847 cell clusters and reveals at least 14 age-biased clusters that are mostly glial types. At the broader cell subclass and supertype levels, we find age-associated gene expression signatures and provide a list of 2,449 unique differentially expressed genes (age-DE genes) for many neuronal and non-neuronal cell types. Whereas most age-DE genes are unique to specific cell types, we observe common signatures with ageing across cell types, including a decrease in expression of genes related to neuronal structure and function in many neuron types, major astrocyte types and mature oligodendrocytes, and an increase in expression of genes related to immune function, antigen presentation, inflammation, and cell motility in immune cell types and some vascular cell types. Finally, we observe that some of the cell types that demonstrate the greatest sensitivity to ageing are concentrated around the third ventricle in the hypothalamus, including tanycytes, ependymal cells, and certain neuron types in the arcuate nucleus, dorsomedial nucleus and paraventricular nucleus that express genes canonically related to energy homeostasis. Many of these types demonstrate both a decrease in neuronal function and an increase in immune response. These findings suggest that the third ventricle in the hypothalamus may be a hub for ageing in the mouse brain. Overall, this study systematically delineates a dynamic landscape of cell-type-specific transcriptomic changes in the brain associated with normal ageing that will serve as a foundation for the investigation of functional changes in ageing and the interaction of ageing and disease.

DOI: 10.1038/s41586-024-08350-8

Source: https://www.nature.com/articles/s41586-024-08350-8