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利用单细胞转录组学描绘阿尔茨海默病大脑中的细胞间通讯失调特征。

Characterizing dysregulations via cell-cell communications in Alzheimer's brains using single-cell transcriptomes.

机构信息

Department of Computer Science, University of California, Irvine, CA, USA.

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

出版信息

BMC Neurosci. 2024 May 13;25(1):24. doi: 10.1186/s12868-024-00867-y.

Abstract

BACKGROUND

Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting 44 million people worldwide, leading to cognitive decline, memory loss, and significant impairment in daily functioning. The recent single-cell sequencing technology has revolutionized genetic and genomic resolution by enabling scientists to explore the diversity of gene expression patterns at the finest resolution. Most existing studies have solely focused on molecular perturbations within each cell, but cells live in microenvironments rather than in isolated entities. Here, we leveraged the large-scale and publicly available single-nucleus RNA sequencing in the human prefrontal cortex to investigate cell-to-cell communication in healthy brains and their perturbations in AD. We uniformly processed the snRNA-seq with strict QCs and labeled canonical cell types consistent with the definitions from the BRAIN Initiative Cell Census Network. From ligand and receptor gene expression, we built a high-confidence cell-to-cell communication network to investigate signaling differences between AD and healthy brains.

RESULTS

Specifically, we first performed broad communication pattern analyses to highlight that biologically related cell types in normal brains rely on largely overlapping signaling networks and that the AD brain exhibits the irregular inter-mixing of cell types and signaling pathways. Secondly, we performed a more focused cell-type-centric analysis and found that excitatory neurons in AD have significantly increased their communications to inhibitory neurons, while inhibitory neurons and other non-neuronal cells globally decreased theirs to all cells. Then, we delved deeper with a signaling-centric view, showing that canonical signaling pathways CSF, TGFβ, and CX3C are significantly dysregulated in their signaling to the cell type microglia/PVM and from endothelial to neuronal cells for the WNT pathway. Finally, after extracting 23 known AD risk genes, our intracellular communication analysis revealed a strong connection of extracellular ligand genes APP, APOE, and PSEN1 to intracellular AD risk genes TREM2, ABCA1, and APP in the communication from astrocytes and microglia to neurons.

CONCLUSIONS

In summary, with the novel advances in single-cell sequencing technologies, we show that cellular signaling is regulated in a cell-type-specific manner and that improper regulation of extracellular signaling genes is linked to intracellular risk genes, giving the mechanistic intra- and inter-cellular picture of AD.

摘要

背景

阿尔茨海默病(AD)是一种毁灭性的神经退行性疾病,影响着全球 4400 万人,导致认知能力下降、记忆力丧失以及日常功能严重受损。最近的单细胞测序技术通过使科学家能够以最细微的分辨率探索基因表达模式的多样性,彻底改变了遗传和基因组分辨率。大多数现有研究仅专注于每个细胞内的分子扰动,但细胞生活在微环境中,而不是孤立的实体中。在这里,我们利用大规模的、公开可用的人类前额叶皮层的单细胞 RNA 测序来研究健康大脑中的细胞间通讯及其在 AD 中的扰动。我们通过严格的 QC 统一处理 snRNA-seq,并根据 BRAIN Initiative 细胞普查网络的定义标记规范的细胞类型。从配体和受体基因表达,我们构建了一个高可信度的细胞间通讯网络,以研究 AD 和健康大脑之间的信号差异。

结果

具体来说,我们首先进行了广泛的通讯模式分析,以突出正常大脑中生物学相关的细胞类型依赖于很大程度上重叠的信号网络,并且 AD 大脑表现出细胞类型和信号通路的不规则混合。其次,我们进行了更集中的细胞类型中心分析,发现 AD 中的兴奋性神经元与抑制性神经元的通讯显著增加,而抑制性神经元和其他非神经元细胞与所有细胞的通讯则普遍减少。然后,我们从信号中心的角度深入研究,表明 CSF、TGFβ和 CX3C 等经典信号通路在向小胶质细胞/血管周细胞的信号以及 WNT 通路中内皮细胞向神经元细胞的信号方面存在显著失调。最后,在提取 23 个已知的 AD 风险基因后,我们的细胞内通讯分析显示,细胞外配体基因 APP、APOE 和 PSEN1 与细胞内 AD 风险基因 TREM2、ABCA1 和 APP 之间存在很强的连接,这些基因在从星形胶质细胞和小胶质细胞向神经元的通讯中起作用。

结论

总之,随着单细胞测序技术的新进展,我们表明细胞信号是按细胞类型特异性调节的,细胞外信号基因的不当调节与细胞内风险基因有关,为 AD 的细胞内和细胞间机制提供了图片。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1eb9/11089696/93906fd9a4e9/12868_2024_867_Fig1_HTML.jpg

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