Uncovering plaque-glia niches in human Alzheimer's disease brains using spatial transcriptomics

Amyloid-beta (Aβ) plaques and their associated glial responses are hallmark features of Alzheimer's disease (AD), yet their interactions within the human brain remain poorly defined.

We applied spatial transcriptomics (ST) and immunohistochemistry (IHC) to 78 postmortem brain sections from 21 individuals in the Religious Orders Study and Memory and Aging Project (ROSMAP). We paired ST with histological data and stratified spots into major categories of plaque-glia niches based on Aβ, GFAP, and IBA1 intensity. Leveraging published ROSMAP single-nucleus RNA-seq data, we examined differences in gene expression, cellular composition, and intercellular communication across these niches. Neuronal and glial changes were validated by IHC and quantitative analyses. We further characterized glial responses using gene set enrichment analysis (GSEA) with known mouse glial signatures and human AD-associated microglial states. Finally, we used iPSC-derived multicellular cultures and single-cell RNA sequencing (scRNA-seq) to identify cell types that, upon short-term Aβ exposure, recapitulate the glial responses observed in the human spatial data.

Low-Aβ regions, enriched for diffuse plaques, exhibited transcriptomic profiles consistent with greater neuronal loss than high-Aβ regions. High-glia regions showed increased expression of inflammatory and neurodegenerative pathways. Spatial glial responses aligned with established gene modules, including plaque-induced genes (PIGs), oligodendrocyte (OLIG) responses, disease-associated microglia (DAM), disease-associated astrocytes (DAA), and human AD-associated microglial states, indicating that diverse glial phenotypes emerge around plaques and shape the local immune environment. IHC confirmed elevated neuronal apoptosis near low-Aβ plaques and greater CD68 abundance and synaptic loss near glia-high plaques. In vitro, iPSC-derived microglia-but not astrocytes-exposed to Aβ displayed transcriptomic changes that closely mirrored the glial states identified in our ST dataset.

Our study provides a comprehensive spatial transcriptomic dataset from human AD brain tissue and bridges spatial gene expression with traditional neuropathology. By integrating ST, snRNA-seq, and human multicellular models, we map cellular states and molecular events within plaque-glia niches. This work offers a spatially resolved framework for dissecting plaque-glia interactions and reveals new insights into the cellular and molecular heterogeneity underlying neurodegenerative pathology.

The online version contains supplementary material available at 10.1186/s44477-025-00002-z.