Microglia and bone marrow-derived monocytes are key elements of central nervous system (CNS) inflammation, both capable of enhancing and dampening immune-mediated pathology, as highlighted by their phenotypic and functional heterogeneity across disease. However, the study-specific focus on individual cell types, disease models or experimental approaches has compartmentalized our knowledge, limiting our ability to infer common and disease-specific responses. This meta-analysis integrates transcriptomic datasets from multiple sequencing methodologies to build a comprehensive resource connecting myeloid responses across six models of neuroinflammation. We demonstrate that monocytes adopt a conserved inflammatory program across distinct pathologies, whereas the microglial program is contingent on the disease microenvironment, challenging the notion of a universal microglial disease signature. Cross-disease comparison further revealed Cd81 as a neuroinflammatory-stable gene that accurately identifies microglia in all experimental models. We further demonstrate that despite uniform mRNA expression throughout, this protein is detectable in microglia only under inflammatory conditions, enabling flow cytometric discrimination of microglia from monocyte-derived cells in CNS disease. Together, our meta-analytical approach integrates data across independent research fields and technologies to build a unified perspective about the common and divergent behaviour of myeloid cells across CNS disease that may better guide future analytical approaches across these fields.