Single-cell Transcriptomics in Autoimmune Diseases: Mechanistic Insights, Cross-disease Convergence, and Translational Challenges in Rheumatoid Arthritis, Systemic Lupus Erythematosus, Type 1 Diabetes, and Multiple Sclerosis.

Autoimmune diseases are characterized by loss of immune tolerance and substantial heterogeneity across patients, tissues, and disease stages. Although bulk transcriptomic studies have identified important inflammatory pathways, they cannot directly resolve rare, transitional, and tissue-contextualized cell states that may be relevant to disease mechanisms and therapeutic response. Single-cell RNA sequencing (scRNA-seq) enables transcriptomic profiling at cellular resolution, while complementary multimodal, receptor-repertoire, epigenomic, and spatial approaches can link cellular states to protein phenotype, clonal architecture, regulatory programs, and tissue context. This review critically examines recent single-cell studies in rheumatoid arthritis, systemic lupus erythematosus and lupus nephritis, type 1 diabetes, and multiple sclerosis. Rather than providing a descriptive catalogue of published studies, we assess the strength of available evidence by distinguishing independently replicated findings from observations supported by limited studies, and cross-sectional associations from longitudinal, treatment-response, and functional evidence. Across the selected diseases, studies repeatedly report inflammatory programs involving interferon signaling, chemokine-mediated immune recruitment, and stromal-immune interactions; however, evidence for convergence at the cell-state and regulatory-network levels remains limited, and the extent to which shared signatures represent common pathogenic mechanisms rather than inflammatory context remains uncertain. We evaluate the translational potential of scRNA-seq for biomarker discovery, patient stratification, and treatment response prediction, while considering evidence from related tissue-based molecular stratification approaches, including the R4RA randomized trial in rheumatoid arthritis. R4RA provides prospective randomized evidence that synovial molecular features can enrich for differential therapeutic responses, but its use of bulk synovial transcriptomics and histopathology does not constitute prospective validation of single-cell-derived biomarkers. We further highlight cohort biases, reproducibility challenges, dissociation artifacts, computational ambiguity, and privacy concerns that constrain immediate clinical implementation. Together, these advances position single-cell profiling as a mechanistic discovery platform with substantial translational promise, contingent on standardization, validation across diverse cohorts, and integration with functional perturbation approaches.