Spatial transcriptomics of human middle temporal gyrus reveals layer‐specific gene expression in early Alzheimer's disease. (December 2021)

• Record Type: Journal Article
• Authors: Chen, Shuo; Chang, Yuzhou; Li, Liangping; Serrano, Geidy E; Beach, Thomas G; Duff, Karen E; Ma, Qin; Fu, Hongjun
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.050540
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: In many neurodegenerative diseases including Alzheimer's disease (AD), specific subpopulations of cells and brain regions are more sensitive to dysfunction and degeneration than others. For example, excitatory neurons in the layer 2/3 of middle temporal gyrus (MTG) is particularly vulnerable to degeneration in early AD. The mechanisms underpinning this selective cellular and regional vulnerability, however, are unclear. Recently, the spatially resolved transcriptomics has been used in AD‐like mouse models to identify genes altered in the vicinity of amyloid plaques and genes differentially expressed in those vulnerable regions in AD. Here we report that spatial transcriptomics of human postmortem MTG reveals differential gene expression in layer 2/3 of early AD compared to non‐AD cases. Methods: Human MTG frozen sections from 2 non‐AD and 2 early AD cases were mounted over the capture areas with poly T probes on the 10x Visium Gene Expression slide. The cDNA libraries were generated by following the 10x Visium Spatial Gene Expression Reagent Kits user guide. Then cDNA libraries from 4 samples were pooled in a NovaSeq6000 SP v1.0 flowcell and paired end sequencing were performed on an Illumina NovaSeq6000 sequencer. The sequence data were analyzed via 10x Genomics software (Space Ranger v 4.0.0 and Loupe Browser v 4.1.0) and Seurat (v 3.2.2). Results: Uniform Manifold Approximation and Projection (UMAP) analysis of spatial transcriptomics data generated seven cell clusters, which correspond to the cortical layers 1‐6 and the white matter in MTG. In the identified differentially expressed genes (DEGs) in layer 2/3, we found many signatures associated with AD including plaque‐induced genes, disease associated microglia genes, oligodendrocyte response genes, A1 astrocyte genes, as well as tangle‐associated genes. GO enrichment analysis of these DEGs revealed important functional pathways that may be implicated in the pathogenesis of AD, such as synapse structure or activity, protein folding and stability, neuronal apoptosis, autophagy, ER stress, oxidative stress, response to amyloid‐beta, microglial activation, neuroinflammatory response, regulation of chemotaxis, and myelination. Conclusions: Taken together, we demonstrate that the genome‐wide the spatially resolved transcriptomics provide an unprecedented and unbiased approach to untangle the selective cellular and regional vulnerability in early AD.