Single-Cell RNA-Sequencing Integration Analysis Revealed Immune Cell Heterogeneity in Five Human Autoimmune Diseases

作者：Siweier Luo, Le Wang, Yi Xiao, Chunwei Cao, Qinghua Liu, Yiming Zhou · 发表于：BIO Integration · 年份：2023 · DOI：10.15212/bioi-2023-0012 · 被引用次数：28 · 研究领域：Systemic Lupus Erythematosus Research、Single-cell and spatial transcriptomics、Extracellular vesicles in disease

Abstract Background: Autoimmune diseases are a group of diseases caused by abnormal immune responses to functional body parts. Single-cell RNA-sequencing (scRNA-seq) technology provides transcriptomic information at the single-cell resolution, thus offering a new way to study autoimmune diseases. Most single-cell RNA-seq studies, however, have often focused on one type of autoimmune disease. Methods: We integrated scRNA-seq data from peripheral blood cells of five different autoimmune diseases (IgA nephropathy [IgAN], Kawasaki disease [KD], multiple sclerosis [MS], Sjogren’s syndrome [SS], and systemic lupus erythematosus [SLE]). We performed dimensionality clustering, cellular communication analysis, re-clustering analysis of monocytes, NK cell populations, differential gene expression analysis, and functional enrichment for all immune cells in these data. Results: We integrated the scRNA-seq results of peripheral blood cells from five different autoimmune diseases (IgAN, KD, MS, SS, and SLE). We showed that all samples contained 18 different immune cell subsets, although the cell cluster populations were different among the 5 diseases. Through intercellular communication network analysis, we determined that the signals of classical and non-classical monocytes were significantly enhanced in patients with IgAN and SLE. The signals of naïve B cells were increased in patients KD. Interestingly, the signals of NK and NK-T cells were enhanced in patients with SS, but reduced in p...