School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100069, China.
Chinese Institute for Brain Research, Beijing 102206, China.
Biomolecules. 2023 Apr 19;13(4):692. doi: 10.3390/biom13040692.
The dysfunction of astrocytes in response to environmental factors contributes to many neurological diseases by impacting neuroinflammation responses, glutamate and ion homeostasis, and cholesterol and sphingolipid metabolism, which calls for comprehensive and high-resolution analysis. However, single-cell transcriptome analyses of astrocytes have been hampered by the sparseness of human brain specimens. Here, we demonstrate how large-scale integration of multi-omics data, including single-cell and spatial transcriptomic and proteomic data, overcomes these limitations. We created a single-cell transcriptomic dataset of human brains by integration, consensus annotation, and analyzing 302 publicly available single-cell RNA-sequencing (scRNA-seq) datasets, highlighting the power to resolve previously unidentifiable astrocyte subpopulations. The resulting dataset includes nearly one million cells that span a wide variety of diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), multiple sclerosis (MS), epilepsy (Epi), and chronic traumatic encephalopathy (CTE). We profiled the astrocytes at three levels, subtype compositions, regulatory modules, and cell-cell communications, and comprehensively depicted the heterogeneity of pathological astrocytes. We constructed seven transcriptomic modules that are involved in the onset and progress of disease development, such as the M2 ECM and M4 stress modules. We validated that the M2 ECM module could furnish potential markers for AD early diagnosis at both the transcriptome and protein levels. In order to accomplish a high-resolution, local identification of astrocyte subtypes, we also carried out a spatial transcriptome analysis of mouse brains using the integrated dataset as a reference. We found that astrocyte subtypes are regionally heterogeneous. We identified dynamic cell-cell interactions in different disorders and found that astrocytes participate in key signaling pathways, such as NRG3-ERBB4, in epilepsy. Our work supports the utility of large-scale integration of single-cell transcriptomic data, which offers new insights into underlying multiple CNS disease mechanisms where astrocytes are involved.
星形胶质细胞对环境因素的功能障碍通过影响神经炎症反应、谷氨酸和离子稳态以及胆固醇和鞘脂代谢，导致许多神经退行性疾病的发生。这需要全面和高分辨率的分析。然而，星形胶质细胞的单细胞转录组分析受到人脑标本稀疏的限制。在这里，我们展示了如何通过整合多组学数据，包括单细胞和空间转录组学和蛋白质组学数据，克服这些限制。我们通过整合、共识注释和分析 302 个公开的单细胞 RNA 测序 (scRNA-seq) 数据集，创建了一个人类大脑的单细胞转录组数据集，突出了能够解决以前无法识别的星形胶质细胞亚群的能力。该数据集包括近 100 万个细胞，涵盖了广泛的疾病，包括阿尔茨海默病 (AD)、帕金森病 (PD)、亨廷顿病 (HD)、多发性硬化症 (MS)、癫痫 (Epi) 和慢性创伤性脑病 (CTE)。我们在三个层面上对星形胶质细胞进行了分析，包括亚型组成、调节模块和细胞间通讯，并全面描述了病理性星形胶质细胞的异质性。我们构建了七个与疾病发生和发展相关的转录组模块，如 M2 ECM 和 M4 应激模块。我们验证了 M2 ECM 模块可以在转录组和蛋白质水平为 AD 的早期诊断提供潜在的标志物。为了实现对星形胶质细胞亚型的高分辨率、局部鉴定，我们还使用整合后的数据集作为参考，对小鼠大脑进行了空间转录组分析。我们发现星形胶质细胞亚型在区域上存在异质性。我们在不同疾病中发现了动态的细胞间相互作用，并发现星形胶质细胞参与了关键的信号通路，如癫痫中的 NRG3-ERBB4。我们的工作支持大规模整合单细胞转录组数据的实用性，这为涉及星形胶质细胞的多种中枢神经系统疾病机制提供了新的见解。
