Assistant Professor University of Oklahoma Norman, Oklahoma, United States
Disclosure(s):
Marmar Moussa, PhD: No financial relationships to disclose
Introduction/Rationale: Microglia are resident immune cells in the central nervous system and a heterogenous population with notable heterogeneity across development phases, regions, and disease states. While a few 'microglia' single cell atlases have recently emerged to profile large microglia datasets, a comprehensive, single cell/nuclei-resolution map of microglial subtypes and functional or activation states across different species remains lacking, especially one that performs an integrative secondary analysis of existing data.
Methods: Here, we present a cross-species single-cell transcriptomic atlas of microglia from mouse and human brains, spanning multiple regions, sexes and ages. We use integrated analysis of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics datasets and tackle computational challenges like batch effect and modality integration.
Results: Our dataset encompasses over 200,000 microglial cells from adult human postmortem brains and sex as well as age-matched murine counterparts. We benchmark several integration approaches using anchor-based and deep manifold alignment methods. Our secondary analysis reveals a core set of conserved microglial subtypes, including homeostatic microglia (TMEM119⁺, P2RY12⁺), interferon-responsive microglia (ISG15⁺, IFIT3⁺), and phagocytic/activated states (CD68⁺, APOE⁺, CST7⁺). Notably, we identify a conserved ‘lipid-associated microglia’ (LAM) state marked by high APOE, TREM2, and GPNMB expression in both species, enriched in aging and neurodegenerative conditions.
Conclusion: Our dataset collection, which is available via a web-interactive atlas tool, provides a valuable resource for understanding microglial diversity across species and lays the foundation for translating findings from mouse models to human. These findings support the existence of evolutionarily conserved microglial programs and highlight the need for caution when extrapolating mouse microglial states to human contexts.
