Using Biological Processes as Prior Knowledge Identifies New Microglial Immune Signatures at Single Cell Level in Alzheimer's Disease.

The brain’s resident immune cells, microglia, play important roles in the pathological process of Alzheimer's disease (AD). Upon encountering amyloid-β (Aβ) plaque accumulation, microglia change its state to produce proinflammatory cytokines to uptake and clear Aβ but during the chronic state of neuroinflammation they become responsible for neurodegeneration. In this paper we propose a new method of analyzing microglia undergoing multi-stage state changes from homeostasis (HOM) to disease associated microglia (DAM). Our single cell gene expression data analysis method differs from the conventional marker based subtyping methods in the sense that it uses prior knowledge, namely, Gene Ontology’s Biological Processes known for immune functions and other related ones. In this regard, our method can be thought of supervised clustering rather than UMAP/tSNE style unbiased subgrouping of cells. The strengths of this "prior knowledge" using method are multi-faceted: (i) one can assign meaningful functional nomenclatures to identified subtypes of cells, (ii) one can refine GO Biological Process genes to be context-specific (e.g., phagocytosis responsible by "microglia" as opposed to "general immune cells"), and (iii) additional context-specific biological processes can be identified in addition to the ones used as "prior knowledge". We illustrate the advantages of our semi-supervised cell clustering method using a set of publicly available human AD and mouse AD model gene expression datasets.