bioRxivImmunologyPreprint
Ancestry-specific rewiring of BCR-MAPK signaling in sarcoidosis B cells
Christopher M. DunniD, Caleb Watkins, Gideon B Hallum, Nathan P. Pezant, Astrid RasmusseniD, Patrick M. GaffneyiD, Harini BagavantiD, Umesh S. DeshmukhiD, Courtney G. MontgomeryiD
Abstract
Sarcoidosis is a heterogenous disease of unknown etiology characterized by non-caseating granulomas. Disease prevalence and presentation vary significantly by ancestry and ranges from acute, self-resolving disease to severe, chronic disease. Following previous reports suggesting B cells in the development and pathogenesis of sarcoidosis, we present here results of single-cell RNA sequencing, supporting B cell involvement in sarcoidosis through altered immediate early response, rewiring of MAPK signaling, and ancestry-specific preferential expansion of B cell receptors. Peripheral blood mononuclear cells were obtained from individuals of African or European Ancestry (AA and EA, respectively) including 48 healthy controls, 59 sarcoidosis patients, and 28 systemic lupus erythematosus (SLE) patients. SLE samples were used as a disease control. Differential expression analysis highlighted many differentially expressed genes (DEGs) with almost 5x more in the AA sarcoidosis versus AA control group compared to the EA sarcoidosis versus EA control group. B cells had the most DEGs of all cell types and expression patterns were similar between ancestries, however, sarcoidosis had an opposite transcription pattern than SLE, demonstrating an alternative immune response to acute activation than that seen in a prototypical autoinflammatory disease. This trend was maintained when examining specialized B cell subsets, with the most pronounced effect in the AA sarcoidosis versus AA control comparison. Our results strongly support further investigation of the role of humoral immune response in sarcoidosis and the potential to highlight patient groups likely to benefit from existing B cell therapies.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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