Integrating transcriptomic datasets across neurological disease identifies unique myeloid subpopulations driving disease-specific signatures

Microglia and bone marrow-derived monocytes are key elements of central nervous system (CNS) inflammation, both capable of enhancing and dampening immune-mediated pathology. However, the study-specific focus on individual cell types, disease models or experimental approaches has limited our ability to infer common and disease-specific responses. This meta-analysis integrates bulk and single-cell transcriptomic datasets of microglia and monocytes from disease models of autoimmunity, neurodegeneration, sterile injury, and infection to build a comprehensive resource connecting myeloid responses across CNS disease. We demonstrate that the bulk microglial and monocyte program is highly contingent on the disease environment, challenging the notion of a universal microglial disease signature. Integration of six single-cell RNA-sequencing datasets revealed that these disease-specific signatures are likely driven by differing proportions of unique myeloid subpopulations that were individually expanded in different disease settings. These subsets were functionally-defined as neurodegeneration-associated, inflammatory, interferon-responsive, phagocytic, antigen-presenting, and lipopolysaccharide-responsive cellular states, revealing a core set of myeloid responses at the single-cell level that are conserved across CNS pathology. Showcasing the predictive and practical value of this resource, we performed differential expression analysis on microglia and monocytes across disease and identified Cd81 as a new neuroinflammatory-stable gene that accurately identified microglia and distinguished them from monocyte-derived cells across all experimental models at both the bulk and single-cell level. Together, this resource dissects the influence of disease environment on shared immune response programmes to build a unified perspective of myeloid behavior across CNS pathology.

Automated summary

Microglia and bone marrow-derived monocytes play important roles in CNS inflammation, but the focus on specific cell types or disease models has limited our understanding of common and disease-specific responses. This meta-analysis integrates transcriptomic data from disease models to provide a comprehensive view of myeloid responses across CNS disease. It reveals that the microglial and monocyte program is influenced by the disease environment, and different disease settings lead to expansion of unique myeloid subpopulations. These subpopulations have specific functional states and are conserved across CNS pathology. The resource also identifies a new neuroinflammatory-stable gene, Cd81, that accurately distinguishes microglia from monocyte-derived cells.