Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

Abstract

Human middle temporal gyrus (MTG) is a vulnerable brain region in early Alzheimer’s disease (AD), but little is known about the molecular mechanisms underlying this regional vulnerability. Here we utilize the 10 × Visium platform to define the spatial transcriptomic profile in both AD and control (CT) MTG. We identify unique marker genes for cortical layers and the white matter, and layer-specific differentially expressed genes (DEGs) in human AD compared to CT. Deconvolution of the Visium spots showcases the significant difference in particular cell types among cortical layers and the white matter. Gene co-expression analyses reveal eight gene modules, four of which have significantly altered co-expression patterns in the presence of AD pathology. The co-expression patterns of hub genes and enriched pathways in the presence of AD pathology indicate an important role of cell–cell-communications among microglia, oligodendrocytes, astrocytes, and neurons, which may contribute to the cellular and regional vulnerability in early AD. Using single-molecule fluorescent in situ hybridization, we validated the cell-type-specific expression of three novel DEGs (e.g., KIF5A, PAQR6, and SLC1A3) and eleven previously reported DEGs associated with AD pathology (i.e., amyloid beta plaques and intraneuronal neurofibrillary tangles or neuropil threads) at the single cell level. Our results may contribute to the understanding of the complex architecture and neuronal and glial response to AD pathology of this vulnerable brain region.

Systematic analysis of cellular crosstalk reveals a role for SEMA6D-TREM2 regulating microglial function in Alzheimer’s disease

“…Our previous findings that the TREM2 sub-network was among the most negatively associated with advanced AD stages motivated us to better understand how its expression changed as a function of neuropathological burden. To do so, we reanalyzed spatial transcriptomics profiles (10X Genomics Visium) from three control and three AD (Braak III and IV) human brains 48 and quantified the effects of local neuropathology, in particular proximity to Aβ plaques, in relation to gene expression patterns ( Figure 2i ).…”

“…We processed the raw count matrices from the 10X Genomics Visium data as described in the original study 48 . Briefly, we used only spots that passed QC in the original study and applied the SCT integration pipeline from Seurat to integrate data across donors.…”

Application of spatial transcriptome technologies to neurological diseases

“…The existence of interactions between plaque and microglia genes is confirmed by this genotype-dependent dependence on plaque contact. In addition, genes differentially expressed in regions associated with pathological changes in AD have been studied using spatial transcriptomics, which may contribute to regional vulnerability in early AD (Chen et al, 2022a). For example, many AD-related signals, such as plaque-induced genes, diseaseassociated microglia genes, oligodendrocyte-responsive genes, A1 astrocyte genes, and tangle-associated genes, have been identified by ST in the middle temporal gyrus (MTG) 2/3 cortical layer, where excitatory neurons are particularly susceptible to degeneration in early AD.…”

Dimension-agnostic and granularity-based spatially variable gene identification

“…Spatially variable genes (SVGs) are biologically significant as they exhibit variations in expression levels across different regions or cell types within a tissue, indicating their involvement in specific biological processes or functions unique to those regions or cell types. Hence, the inference of SVGs can help researchers gain a deeper understanding of how different cell types and genes contribute to the overall structures and functions of tissues in normal or disease states 10 . Additionally, SVGs can be used as molecular markers to track developmental or disease-related changes in the spatial distribution of specific cell types.…”