Background/Purpose: Rheumatologic diseases are characterized by distinct clinical presentations and patterns of organ involvement, yet share many genetic risk factors and treatment responses. This suggests that although etiologies may be multifactorial, there are likely shared mechanisms across autoimmunity. Prior single cell genomic studies have predominantly been disease-specific or captured only a small subset of rheumatic diseases. The goals of this study were to identify both unique and shared mechanisms of autoimmunity across a wide-array of diseases using single-cell RNA sequencing (scRNAseq), including both tissue-specific and systemic autoimmune diseases. We also integrated patients with checkpoint inhibitor toxicities to gain insight into biological determinants driving the break of immune tolerance in de novo autoimmunity.

Methods: ScRNAseq was generated (10x Genomics) with paired surface protein (n=204 targets; CITE-seq protocol) for a minimum of 20 patients per disease: Systemic Lupus Erythematosus (SLE), Rheumatoid Arthritis, IgG4-related disease, Graves’ Disease, Hashimoto’s Disease, Multiple Sclerosis (MS), Type 1 Diabetes, Celiac Disease, and checkpoint inhibitor related diabetes and thyroiditis. Sequencing data (Illumina NovaSeq X) was aligned, processed (CellRanger V6.0.2) and integrated (Harmony). Upon defining cell subsets across lineages with iterative clustering strategies, downstream analysis focused on cellular and transcriptional programs that are shared and distinct across disease. Differential cell-type abundance was assessed by a mixed effects logistic regression model (MASC) and differentially expressed gene analysis was performed (DESeq2).

Results: We analyzed 3,542,103 cells after quality-control filtering and identified an initial set of 45 distinct cell types across lineages. Differential abundance analysis highlighted expected alterations in SLE (reduction in CD4⁺ T cells; expansion of B cells) while also providing greater resolution on the specific cell types involved (specific reductions in RORC⁺ CD4+ T cells and proliferating plasma cells). We identified novel findings such as expansion of a monocyte subset with prominent interferon signature in MS, celiac and type 1 diabetes, reduction of pDCs in IgG4-related disease, and reduction of CD4⁺ T cells with a Treg signature across diseases. Comparing gene expression in healthy and disease highlighted that many genes were differentially expressed in B cell subsets in Hashimoto’s and Graves’ disease ( >350 each) whereas relatively fewer were altered in checkpoint-associated thyroiditis (< 100 each), highlighting distinct biology despite similar clinical presentations. Ongoing analysis looking at gene programs and integrating cell surface protein expression, TCR and BCR sequencing will enable further definition of key drivers of autoimmunity.  

Conclusion: Our cross-disease analytical strategies enabled identification of several shared and distinct biological programs, which ultimately may help nominate novel drug targets relevant to multiple autoimmune diseases, further emphasizing the importance of cross-discipline collaborations in addition to disease-specific study.

« Back to ACR Convergence 2024

ACR Meeting Abstracts - https://acrabstracts.org/abstract/shared-and-disease-specific-mechanisms-of-autoimmunity-using-single-cell-sequencing-of-peripheral-immune-cells/