Instructor Massachusetts Gen. Hosp., Harvard Med. Sch. Boston, Massachusetts, United States
Disclosure(s):
Jacquelyn Nestor, MD, PhD: No relevant disclosure to display
Introduction/Rationale: Autoimmunity is defined by disruption of the immune system, where instead of defending the body, the immune system turns on itself and attacks its own organs instead. While this immune dysfunction connects autoimmune diseases, each disease is distinguished by the organs involved and clinical features that characterize its presentation. The goals of this study are to utilize single-cell sequencing technologies to characterize peripheral immune cells and identify shared and unique mechanisms of autoimmunity.
Methods: To typify shared mechanisms of autoimmunity, samples were obtained across healthy controls and multiple diseases: Lupus, RA, IgG4-RD, Graves’ Disease, Hashimoto’s Disease, MS, T1D, Celiac Disease and ICI-related diabetes and thyroiditis. PBMCs were used to generate scRNAseq and paired protein data (10x Genomics). In-house data and multiple external data sets were aligned to the same genome and integrated (Harmony). Iterative clustering was used to distinguish cell subsets. Further downstream analysis includes abundance, differentially expressed gene analysis, and identification of cellular and transcriptional programs.
Results: Using the above pipeline we characterized 3.5M peripheral immune cells and identified 45 unique cell subsets. We are able to both redemonstrate known biology such as CD4+ lymphopenia across multiple autoimmune diseases, and highlight novel disease-specific findings such as monocyte subset expansion with interferon signature in a subset of diseases. The single-cell data also enables mapping the cellular context of autoimmune disease GWAS susceptibility variants, furthering our understanding of disease pathogenesis.
Conclusion: Our initial results demonstrate that autoimmune diseases have shared mechanisms that broadly propagate autoimmunity and unique transcriptional mechanisms that can drive specific disease states. Further definition of these shared and unique pathways can lead to the discovery of cross-disease and disease-specific therapeutic targets.
