High-Resolution Spatial Profiling of Microglia Reveals Proximity Associated Immunometabolic Reprogramming in Alzheimers Disease

Saito, K.; Goulding, D. S.; Nolt, G. L.; Dimas, S. H.; Moore, L. C.; Stevens, I. O.; Anderson, S.; Snipes, A.; Macauley, S. L.; Nelson, P. T.; Johnson, L.; Morganti, J.

doi:10.1101/2025.05.16.654329

bioRxiv · 10.1101/2025.05.16.654329

High-Resolution Spatial Profiling of Microglia Reveals Proximity Associated Immunometabolic Reprogramming in Alzheimers Disease

Saito, K.·Goulding, D. S.·Nolt, G. L.·Dimas, S. H.·Moore, L. C.·Stevens, I. O.·Anderson, S.·Snipes, A.·Macauley, S. L.·Nelson, P. T.·Johnson, L.·Morganti, J.

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Abstract

Single-cell RNA sequencing has demonstrated that the presence of parenchymal amyloid plaques and intracellular hyperphosphorylated tau pathology is associated with distinctive (and possibly disease-driving) microglial heterogeneity. However, our understanding of how proximity to these Alzheimers disease (AD) pathological hallmarks in situ relates to microglial gene expression remains obscure. Here, we utilized high-resolution spatial transcriptomics (ST) via the Xenium platform with a fully customized gene panel to elucidate disease-associated microglial subtypes in tandem with examining metabolic signatures across AD-relevant mouse models and well-characterized human postmortem tissue. Three mouse models were evaluated: PS19, APP/PS1, and 5xFAD. Analyzing anatomical features across entire hemisections, our approach resolved the distribution of five disease-associated microglial subtypes, while deciphering how proximity to cerebral amyloid plaques influenced transcriptional mediators governing metabolic pathways. We observed robust alterations in glycolytic and cholesterol/lipid processing pathways in plaque-associated microglia, consistent with a specific switch to glycolysis and lipid-fueled metabolism in the plaque niche. Extending our analysis to human postmortem dorsolateral prefrontal cortex (dlPFC), we identified conserved disease-reactive microglial states, i.e., similar proximity-dependent metabolic shifts around amyloid plaques. Further, integrating spatial transcriptomics with machine-learning approaches revealed novel anatomic domain-specific cellular gene expression profiling features, highlighting differential vulnerabilities of neuronal, glial, and vascular populations near specific microglial subtypes. Together, our findings provide one of the first comprehensive and high-resolution atlas of microglial immunometabolic states across species, anatomical regions, and AD pathological burden.

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Saito, K., Goulding, D. S., Nolt, G. L., Dimas, S. H., Moore, L. C., Stevens, I. O., Anderson, S., Snipes, A., Macauley, S. L., Nelson, P. T., Johnson, L., Morganti, J.. 2025-05-16. High-Resolution Spatial Profiling of Microglia Reveals Proximity Associated Immunometabolic Reprogramming in Alzheimers Disease. https://doi.org/10.1101/2025.05.16.654329

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