Miyoshi Emily, Morabito Samuel, Henningfield Caden M, Das Sudeshna, Rahimzadeh Negin, Shabestari Sepideh Kiani, Michael Neethu, Emerson Nora, Reese Fairlie, Shi Zechuan, Cao Zhenkun, Srinivasan Shushrruth Sai, Scarfone Vanessa M, Arreola Miguel A, Lu Jackie, Wright Sierra, Silva Justine, Leavy Kelsey, Lott Ira T, Doran Eric, Yong William H, Shahin Saba, Perez-Rosendahl Mari, Head Elizabeth, Green Kim N, Swarup Vivek
Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA.
Institute for Memory Impairments and Neurological Disorders (MIND), University of California, Irvine, Irvine, CA, USA.
Nat Genet. 2024 Dec;56(12):2704-2717. doi: 10.1038/s41588-024-01961-x. Epub 2024 Nov 22.
The pathogenesis of Alzheimer's disease (AD) depends on environmental and heritable factors, with its molecular etiology still unclear. Here we present a spatial transcriptomic (ST) and single-nucleus transcriptomic survey of late-onset sporadic AD and AD in Down syndrome (DSAD). Studying DSAD provides an opportunity to enhance our understanding of the AD transcriptome, potentially bridging the gap between genetic mouse models and sporadic AD. We identified transcriptomic changes that may underlie cortical layer-preferential pathology accumulation. Spatial co-expression network analyses revealed transient and regionally restricted disease processes, including a glial inflammatory program dysregulated in upper cortical layers and implicated in AD genetic risk and amyloid-associated processes. Cell-cell communication analysis further contextualized this gene program in dysregulated signaling networks. Finally, we generated ST data from an amyloid AD mouse model to identify cross-species amyloid-proximal transcriptomic changes with conformational context.
阿尔茨海默病(AD)的发病机制取决于环境和遗传因素,其分子病因仍不清楚。在此,我们展示了对晚发性散发性AD和唐氏综合征相关AD(DSAD)的空间转录组学(ST)和单核转录组学研究。研究DSAD为增强我们对AD转录组的理解提供了一个机会,有可能弥合基因小鼠模型与散发性AD之间的差距。我们确定了可能是皮层层优先病理积累基础的转录组变化。空间共表达网络分析揭示了短暂的和区域受限的疾病过程,包括在上皮层层失调的神经胶质炎症程序,该程序与AD遗传风险和淀粉样蛋白相关过程有关。细胞间通讯分析进一步将该基因程序置于失调的信号网络背景中。最后,我们从淀粉样蛋白AD小鼠模型生成了ST数据,以识别具有构象背景的跨物种淀粉样蛋白近端转录组变化。