Understanding rheumatic disease through continuous cell state analysis

Autoimmune rheumatic diseases are a heterogeneous group of conditions, including rheumatoid arthritis (RA) and systemic lupus erythematosus. With the increasing availability of large single-cell datasets, novel disease-associated cell types continue to be identified and characterized at multiple omics layers, for example, 'T peripheral helper' (T_PH) (CXCR5^- PD-1^hi) cells in RA and systemic lupus erythematosus and MerTK⁺ myeloid cells in RA. Despite efforts to define disease-relevant cell atlases, the very definition of a 'cell type' or 'lineage' has proven controversial as higher resolution assays emerge. This Review explores the cell types and states involved in disease pathogenesis, with a focus on the shifting perspectives on immune and stromal cell taxonomy. These understandings of cell identity are closely related to the computational methods adopted for analysis, with implications for the interpretation of single-cell data. Understanding the underlying cellular architecture of disease is also crucial for therapeutic research as ambiguity hinders translation to the clinical setting. We discuss the implications of different frameworks for cell identity for disease treatment and the discovery of predictive biomarkers for stratified medicine - an unmet clinical need for autoimmune rheumatic diseases.